Technology on Towards Freedom

New Approach Methodologies

Tue, 24 Mar 2026 15:24:28 -0700

This is a webpage compiled from comprehensive reports by Perplexity, Gemini, Mistral AIs, as well as a NAM summary by Dr. Zheng Tan on validated medical developments as of <2026-03-24 Tue>.

Preamble

The discovery items have been compiled and organized by Mistral AI into 7 themes:

AI-Driven Drug Discovery & Repurposing
Organ-on-a-Chip & Microphysiological Systems
Human Organoids & Organoid-Based Models
In Silico Modeling, PBPK, and Computational Methods
High-Throughput & Omics-Based Approaches
Toxicology & Safety Assessment via NAMs
Regulatory & Industry Adoption of NAMs

Each item is presented in a consistent format:
Discovery
Validation
Impact
References

A summary table and conclusion are provided at the end of this webpage.Please note that the term NAM is used to cover a wide range of items including those that can be said to be NAM-enabling.

Here are the AI reports:
NAM-gemini.pdf
NAM-mistral.pdf
NAM-perplexity.pdf

Here is the NAM summary document kindly created by Dr. Zheng Tan which contains additional insights for several items such as:
Development Team
Country
Significance of NAM discovery

The graphic was generated by Mistral and represents a microscopic view of organoid and NAM technology.

Introduction

New Approach Methodologies (NAMs) represent a paradigm shift in biomedical research and drug development, replacing or supplementing traditional animal testing with human-relevant, in vitro, in silico, and in chemico technologies. This report synthesizes peer-reviewed, validated medical discoveries enabled by NAMs, organized thematically to highlight their scientific, clinical, and regulatory impact.

1. AI-Driven Drug Discovery & Repurposing

Artificial Intelligence (AI) and machine learning (ML) are revolutionizing drug discovery by analyzing vast datasets to identify novel drug candidates, predict drug responses, and repurpose existing drugs for new therapeutic uses. This section highlights groundbreaking discoveries where AI-driven approaches have accelerated drug development timelines, reduced reliance on animal testing, and provided actionable insights for treating complex diseases such as COVID-19, idiopathic pulmonary fibrosis, and neurodegenerative disorders.

1.1 AI-Powered Drug Repurposing for COVID-19

Discovery: The JAK inhibitor baricitinib (originally approved for rheumatoid arthritis) was identified as a potential COVID-19 therapy using an AI-driven in silico NAM. The model predicted its ability to block SARS-CoV-2 infection and modulate cytokine signaling pathways.
Validation: Subsequent clinical trials confirmed that baricitinib, when added to standard care, reduced mortality and improved outcomes in hospitalized COVID-19 patients.
Impact: Demonstrated the power of AI-driven drug repurposing for pandemic response.
References: Can New Approach Methodologies De-Risk Drug Development?

1.2 AI-Designed Novel Drug Candidate for Idiopathic Pulmonary Fibrosis

Discovery: Insilico Medicine’s AI platform designed a novel drug candidate for idiopathic pulmonary fibrosis in just 18 months, integrating multimodal omics data (single-cell transcriptomics, proteomics) with deep generative models and graph neural networks.
Validation: The candidate advanced to Phase II clinical trials, showcasing AI’s ability to accelerate drug discovery timelines.
Impact: Reduced reliance on animal testing and shortened the drug development pipeline.
References: From AI-Assisted In Silico Computational Design to Preclinical In Vivo Models

1.3 Topiramate for Inflammatory Bowel Disease (IBD)

Discovery: Transcriptomic reversal scoring and network pharmacology identified topiramate as a candidate for IBD by predicting its ability to reverse disease-specific expression profiles.
Validation: Further preclinical and clinical studies are ongoing to validate its efficacy.
Impact: Demonstrated the potential of AI-driven repurposing for complex diseases.
References: From Lab to Clinic: Success Stories of Repurposed Drugs in Treating Major Diseases

1.4 Drug Repurposing for Neurodegenerative Disorders

Discovery: High-throughput screening (HTS) identified compounds capable of disrupting 14-3-3 protein interactions, offering potential treatments for Amyotrophic Lateral Sclerosis (ALS).
Validation: AI integrating advanced computational techniques is overcoming the limitations of conventional HTS which are primarily huge volume of compounds and bio-interaction complexities.
Impact: Provided new therapeutic avenues for neurodegenerative diseases with unmet medical needs.
References: AI-driven High Throughput Screening for Targeted Drug Discovery, How AI Contributes to make High-Throughput Screening more Efficient, [New Approach Methodologies Facilitating Drug Discovery](https://www.biotechniques.com/drug-discovery-development/if-sart-nams-an-e xciting-era-for-drug-discovery_sartorius/)

1.5 CoreFinder: AI-Driven Discovery of Biosynthetic Gene Clusters

Discovery: The CoreFinder system, a transformer-based model, predicted biosynthetic gene cluster (BGC) functions in fungi, uncovering novel BGCs validated through in vitro fermentation and LC-MS analysis.
Validation: Demonstrated the ability of AI to drive valid scientific discoveries independently of traditional experimental paradigms.
Impact: Unlocked new biosynthetic pathways for pharmaceutical advancement.
References: Deciphering Biosynthetic Gene Clusters with a Context-aware Protein Language Model

1.6 Disrupting TSLP Signaling as a Treatment for Atopic Diseases

Discovery: Identified putative small molecule inhibitors that disrupt TSLP–TSLP receptor interactions.
Validation: Demonstrated efficacy in human cell assays using in vitro human cell-based drug screening for atopic diseases (e.g., atopic dermatitis, asthma), leading to novel treatment options.
Impact: Provides a human-relevant alternative to animal models for drug discovery in inflammatory skin diseases.
References: Disrupting TSLP-TSLP receptor interactions via putative small molecule inhibitors yields a novel and efficient treatment option for atopic diseases

2. Organ-on-a-Chip & Microphysiological Systems

Organ-on-a-chip and microphysiological systems replicate the dynamic, multi-cellular environments of human organs in microfluidic devices, enabling high-fidelity studies of drug effects, disease mechanisms, and toxicity. By mimicking tissue-tissue interfaces, fluid flow, and mechanical forces, these platforms offer human-relevant alternatives to traditional animal models, driving advances in personalized medicine and regulatory-approved drug development tools.

2.1 Emulate Liver-on-a-Chip Identifies Hepatotoxicity

Discovery: The Emulate liver-on-a-chip model correctly identified hepatotoxicity in 87% of drugs that had tested as safe in animal models but were later found toxic in humans (see Performance assessment link below).
Validation: The platform recapitulated human-specific metabolic dynamics, including albumin secretion and mechanical stimuli in the extracellular matrix.
Impact: Highlighted the superiority of human-relevant microphysiological systems over animal models for predicting drug-induced liver injury (DILI).
References: Tumor organoids for cancer research and personalized medicine, Performance assessment and economic analysis of a human Liver-Chip for predictive toxicology, What are NAMs?

2.2 Acetaminophen (Tylenol) Toxicity Mechanism

Discovery: Liver-on-a-chip technology (see 2.1) equipped with nanotechnology-based optoelectronic sensors identified that acetaminophen blocks cellular respiration in minutes at much lower doses than previously believed, revealing an ultra‑rapid mitochondrial respiration impairment component not captured in legacy in vivo studies.
Validation: Sensors placed inside the bionic tissue detected rapid changes in oxygen uptake at much lower doses than previously believed from decades of animal research.
Impact: Provides a human-specific explanation for rare off-target effects and skin reactions that traditional animal models failed to capture, transforming safety protocols for one of the world’s most common medications.
References: Hepatotoxic assessment in a microphysiological system, What are NAMs?

2.3 Lung-on-a-Chip for Antiviral Efficacy

Discovery: A human lung-on-a-chip system (Emulate Bio) tested RNA-based antiviral therapies for influenza, showing significant reduction in viral replication and inflammatory responses with minimal off-target toxicity.
Validation: Demonstrated efficacy and safety under physiologically relevant conditions (air-liquid interface, dynamic flow).
Impact: Provided a human-relevant platform for antiviral drug testing, overcoming limitations of static cultures and animal models.
References: Lung-On-A-Chip Technologies for Disease Modeling and Drug Development, Human Lung-on-a-Chip Model Demonstrates Potential for Testing Preclinical Influenza Therapeutics, Revolutionizing respiratory health research

2.4 Lung-on-a-Chip for Tumor Heterogeneity & Drug Resistance

Discovery: Microfluidic lung-on-a-chip platforms modeled lung cancer microenvironments, enabling Label-free real-time classification of tumor cells at 10,000 cells/second as well as tracking of drug-resistant subpopulations (e.g., EGFR T790M mutations in non-small-cell lung cancer).
Validation: Demonstrated the ability to observe tumor heterogeneity and resistance dynamics in a human-relevant system.
Impact: Accelerated the development of targeted therapies and personalized treatment strategies.
References: Progress and application of lung-on-a-chip for lung cancer, The potential of lung-on-a-chip as an alternative to animal testing, Microfluidic lung cancer models: Bridging clinical treatment strategies and tumor microenvironment recapitulation

2.5 Liver and Skin Organ-on-a-Chip for PK-PD Studies

Discovery: The HUMIMIC Chip2 integrated liver spheroids and skin models to study pharmacokinetic-pharmacodynamic (PK-PD) relationships under chemical exposure.
Validation: Demonstrated the platform’s utility for quantifying drug metabolism and toxicity in a human-relevant, multi-organ context.
Impact: Supported regulatory acceptance of organ-on-a-chip technologies as drug development tools.
References: Organ-on-a-chip meets artificial intelligence in drug evaluation, Organs-on-Chips in Drug Development: Engineering Foundations, Artificial Intelligence, and Clinical Translation

2.6 ALS Pathogenesis and Early Biomarkers

Discovery: Human spinal cord organ-chips integrated with vascular interfaces modeled early sporadic Amyotrophic Lateral Sclerosis (ALS), uncovering neurofilament dysregulation and synaptic signaling defects.
Validation: Multi-omics analysis confirmed these molecular changes occur before overt neuron loss, mirroring clinical biomarkers that are difficult to detect in animal models.
Impact: Offers a human-relevant platform to study early disease progression and identify therapeutic targets before irreversible nerve damage occurs.
References: Organ-Chip ALS Model Uses Patient iPSCs to Uncover Early Disease Progression, An organ-chip model of sporadic ALS using iPSC

2.7 GABAergic Signaling in Cancer Invasion

Discovery: Patient-derived tumor organ-chips proved that tumor-derived GABA acts as a marker of poor prognosis and directly promotes invasion in metastatic colorectal cancer.
Validation: Interrogating the underlying biology on-chip demonstrated that inhibiting GABA synthesis significantly reduced invasive behavior, capturing patient-specific heterogeneity more faithfully than static cultures.
Impact: Establishes a new therapeutic target for colorectal cancer and validates the ability of organ-chips to replicate the complex tumor microenvironment.
References: GABAergic signaling contributes to tumor cell invasion and poor overall survival in colorectal cancer

2.8 Cervical Protective Role in Dysbiosis

Discovery: Linked Cervix and Vagina Organ-Chips demonstrated that cervical mucus actively modulates vaginal inflammation and protects the epithelium from injury during dysbiosis.
Validation: Exposure to cervix-derived mucus on-chip reduced inflammatory responses and altered protein expression profiles, identifying potential new biomarkers for bacterial vaginosis.
Impact: Uncovers human-specific protective mechanisms that cannot be studied in animal models, facilitating the discovery of new feminine health therapeutics.
References: Cervical mucus in linked human Cervix and Vagina Chips modulates vaginal dysbiosis

2.9 Lung-on-a-Chip Replicates Human Lung Disease and Drug Responses

Discovery: Microfluidic chips lined with human lung cells modeled pulmonary edema, COPD, and drug toxicity.
Validation: Demonstrating superior predictive value over animal models for lung disease and toxicity, it is recognized by the FDA as a valid testing platform for specific drug submissions.
Impact: Enabled more accurate modeling of human lung responses to drugs and diseases.
References: Reconstituting Organ-Level Lung Functions on a Chip, A Human Disease Model of Drug Toxicity–Induced Pulmonary Edema in a Lung-on-a-Chip Microdevice

2.10 Human Skin-Lymphoreticular Model-on-Chip for Inflammatory Skin Diseases

Discovery: Developed a human-based skin-lymphoreticular model-on-chip emulating inflammatory skin conditions capturing immune-skin interactions on a chip platform.
Validation: Demonstrated utility for studying atopic dermatitis and related diseases.
Impact: Eliminates the need for animal models in studying inflammatory skin diseases.
References: A Human‐Based Skin‐Lymphoreticular Model‐on‐Chip to Emulate Inflammatory Skin Conditions

3. Human Organoids & Organoid-Based Models

Human organoids are three-dimensional, self-organizing cultures derived from stem cells that recapitulate the structure and function of human organs. This section showcases how organoids are transforming disease modeling, drug screening, and gene therapy development, enabling precision medicine approaches for conditions like cystic fibrosis, Duchenne muscular dystrophy, and cancer.

3.1 Forskolin-Induced Swelling (FIS) Assay for Cystic Fibrosis

Discovery: Patient-derived intestinal organoids from Cystic Fibrosis (CF) patients were used in the Forskolin-induced Swelling (FIS) assay to test CFTR-modulator drugs.
Validation: The assay accurately predicted clinical trial responses for individual patients, including rare genotypes.
Impact: Enabled tailored therapeutic strategies, significantly increasing life expectancy for CF patients.
References: Towards diagnostic and personalized models using organoids, NAMs: an exciting era for drug discovery

3.2 Patient-Derived Organoids for Gene Therapy in Duchenne Muscular Dystrophy (DMD)

Discovery: A breakthrough workflow converted cryopreserved peripheral blood mononuclear cells (PBMCs) into induced pluripotent stem cells (iPSCs) and then into cardiac organoids within three weeks, correcting unique splicing defects in DMD patients.
Validation: Custom ASOs restored dystrophin expression and improved calcium transients in cardiac organoids.
Impact: Provided a scalable, cost-effective alternative to animal models for developing personalized gene therapies.
References: Patient-Derived Organoids for Gene Therapy Development

3.3 Patient-Derived Organoids for Metastatic Colorectal Cancer (OPTIC Trial)

Discovery: The OPTIC trial validated the predictive power of patient-derived organoids (PDOs) for metastatic colorectal cancer (mCRC) and the PDO response correlated with radiological tumor response and clinical survival outcomes, particularly for oxaliplatin-based chemotherapy.
Validation: Demonstrated 83.3% accuracy in predicting patient survival and tumor response.
Impact: Enabled early identification of ineffective therapies, minimizing patient exposure to toxicity and optimizing treatment selection.
References: Patient-Derived Organoids Predict Treatment Response in Metastatic Colorectal Cancer

3.4 Organoid Immune Co-Culture Models for Cancer Vaccines

Discovery: Tumor organoids co-cultured with autologous peripheral blood lymphocytes simulated the tumor immune microenvironment (TIME), assessing individual responses to checkpoint inhibitors and CAR-T cell therapies.
Validation: Identified tumor-specific antigens with high immunogenicity, enabling the design of personalized cancer vaccines.
Impact: Revolutionized immunotherapy development by capturing spatial organization and immune dynamics.
References: From petri dish to patient care: organoids bring personalised cancer therapy closer

3.5 Kidney Assembloids for Polycystic Kidney Disease (PKD)

Discovery: Researchers generated the most complex kidney structures to date—assembloids combining filtering nephrons with urine-concentrating collecting ducts.
Validation: Assembloids recapitulated key features of PKD, including inflammation and fibrosis, previously irreproducible in animal models.
Impact: Opened new avenues for studying chronic kidney disease and predicting drug-induced nephrotoxicity.
References: Researchers develop most advanced kidney organoid yet for disease modeling and drug discovery

3.6 Miller-Dieker Syndrome (MDS) Root Cause

Discovery: Human brain organoids derived from MDS patient cells identified the root cause of Miller-Dieker Syndrome as early neural stem cell death and severe division defects in “outer radial glia”.
Validation: Time-lapse imaging of patient-derived organoids showed that these specific glia cells—which are entirely absent in mouse models—failed to divide properly.
Impact: Solves a long-standing mystery in rare neurodevelopmental disease that was impossible to investigate using traditional rodent models and proves that patient-derived organoids can bridge the gap between animal models and human pathophysiology.
References: An Organoid-Based Model of Cortical Development Identifies Non-Cell-Autonomous Defects in Wnt Signaling Contributing to Miller-Dieker Syndrome, Cerebral organoids expressing mutant actin genes reveal cellular mechanism underlying microcephaly

3.7 IGF-1 Dependency in Lung Cancer Subtypes

Discovery: A comprehensive library of 40 SCLC organoid lines revealed that non-neuroendocrine small cell lung cancer (SCLC) depends on the insulin-like growth factor 1 (IGF-1) signaling axis for growth.
Validation: Genetic ablation of TP53 and RB1 in human alveolar organoids replicated this dependency, and IGF1R inhibitors were shown to effectively suppress growth in patient-derived models.
Impact: Identifies IGF1R inhibition as a promising new therapeutic strategy for a specific, treatment-resistant patient population.
References: An organoid library unveils subtype-specific IGF-1 dependency via a YAP–AP1 axis in human small cell lung cancer

3.8 Intestinal Organoids Reveal Stem Cell Biology and Disease Mechanisms

Discovery: Developed the first human intestinal organoids from adult stem cells, enabling study of gut disease, cancer, and drug responses in human tissue.
Validation: Extended to liver, kidney, brain, and retinal organoids worldwide.
Impact: Foundational technology for human organoid research.
References: Single Lgr5 stem cells build crypt-villus structures in vitro without a mesenchymal niche

3.9 Brain Organoids Model Microcephaly Caused by Zika Virus

Discovery: Human brain organoids demonstrated Zika virus infection of neural progenitor cells, modeling microcephaly-like features in human tissue.
Validation: Human-specific features of microcephaly were captured by the organoids which mouse models had been unable to fully recapitulate.
Impact: Provided human-specific insights into Zika virus pathology.
References: [Qian et al., Cell 2016; Garcez et al., Science 2016] Brain-Region-Specific Organoids Using Mini-bioreactors for Modeling ZIKV Exposure, Zika virus tested in human brain organoids

4. In Silico Modeling, PBPK, and Computational Methods

In silico modeling—including Physiologically Based Pharmacokinetic (PBPK) models and digital twins—simulates drug behavior in the human body, enabling virtual clinical trials and predictive toxicology. By integrating computational methods with biological data, these approaches reduce reliance on animal testing, optimize dosing regimens, and accelerate the development of safe and effective therapies.

4.1 Physiologically Based Pharmacokinetic (PBPK) Modeling

Discovery: PBPK models integrate in vitro data on absorption, distribution, metabolism, and excretion (ADME) with physiological parameters to predict internal human exposure.
Validation: Correctly estimated systemic exposure of caffeine and coumarin in different product types, demonstrating that model-informed approaches can replace in vivo toxicokinetics.
Impact: Enabled virtual clinical trials and optimized dosing regimens without animal testing.
References: Advancing drug development with “Fit-for-Purpose” modeling informed approaches, SCCS Notes of guidance for the testing of cosmetic ingredients and their safety evaluation, The margin of internal exposure (MOIE) concept for dermal risk assessment based on oral toxicity data - A case study with caffeine, AI-driven virtual cell models in preclinical research, Organs-on-Chips in Drug Development: Engineering Foundations, Artificial Intelligence, and Clinical Translation

4.2 Bioequivalence Bridging for Tofacitinib

Discovery: Pharmacokinetic/pharmacodynamic (PK/PD see 4.1) modeling was used to bridge the immediate-release formulation of tofacitinib to a new extended-release version for ulcerative colitis.
Validation: The computational model successfully established bioequivalence, satisfying regulatory safety and efficacy requirements.
Impact: Supported FDA approval avoiding new Phase 3 clinical trials, significantly accelerating patient access to the new formulation.
References: Integrating Clinical Variability into PBPK Models for Virtual Bioequivalence of Single and Multiple Doses of Tofacitinib Modified-Release Dosage Form, Virtual Bioequivalence Assessment of Tofacitinib Once Daily Modified Release Dosage Form in Pediatric Subjects

4.3 Digital Twins for Clinical Trial Simulation

Discovery: Digital twins are virtual representations of individuals integrating clinical, genetic, and environmental data—promise to revolutionize clinical trial design.
Validation: Simulation of treatment strategies before patient enrollment, reducing risks and costs.
Impact: Could eliminate the need for many traditional clinical trials by predicting patient-specific responses.
References: Increasing acceptance of AI‐generated digital twins through clinical trial applications, The Use of Digital Healthcare Twins in Early-Phase Clinical Trials: Opportunities, Challenges, and Applications, Enhancing randomized clinical trials with digital twins, What are NAMs?

4.4 Quantitative Systems Pharmacology (QSP) Models

Discovery: QSP models combine mechanical simulations of physiology with molecular signaling pathways to predict immunogenicity and pharmacokinetics of complex biologics (e.g., monoclonal antibodies).
Validation: FDA highlighted QSP as a tool to reduce reliance on animal testing for “what-if” scenarios.
Impact: Accelerated the development of biologics and personalized medicine.
References: FDA animal testing phaseout urges AI-based trial alternatives, organoids, other “NAMs”, Beyond lab animals

4.5 AlphaFold Predicts Protein Structures

Discovery: AI-based prediction of protein 3D structures from amino acid sequences transformed structural biology and drug target identification supporting NAM workflows.
Validation: Open-access database covers over 200 million predicted structures with atomic accuracy even when similar architectures had not been previously discovered through animal research.
Impact: Provides data previously requiring years of laboratory work.
References: Highly accurate protein structure prediction with AlphaFold

5. High-Throughput & Omics-Based Approaches

High-throughput technologies such as CRISPR screens, single-cell RNA sequencing, and multi-omics integration enable rapid identification and validation of drug targets, disease mechanisms, and toxicity pathways. This section highlights how omics-based NAMs are reshaping mechanistic understanding and accelerating the discovery of novel therapies for diseases with high unmet medical needs.

5.1 Tox21 Consortium: High-Throughput Chemical Screening

Discovery: The Tox21 federal collaboration uses robotic high-throughput screening (HTS) to evaluate thousands of chemicals simultaneously, generating millions of data points on biological pathways, developing an 18-assay battery for the estrogen receptor (ER) pathway, identifying endocrine-disrupting compounds without animal testing.
Validation: EPA formally accepted this computational model as an alternative to traditional rodent assays.
Impact: Marked the first regulatory prioritization of robotically derived molecular data over animal testing.
References: Tox21: Chemical testing in the 21st century, United States Federal Government TOX21 Collaboration, About Tox21

5.2 Multi-Omics Integration for Toxicity Pathways

Discovery: Integrative NAMs combining genomics, transcriptomics, proteomics, and metabolomics revealed novel: Oxidative stress pathways, Mitochondrial dysfunction signatures, and Immune-modulating pathways.
Validation: Omics-based NAMs distinguished adaptive from adverse responses and generated candidate biomarkers for early detection.
Impact: Reshaped mechanistic understanding of chemical toxicity.
References: Multi-omics integration analysis, The future of pharmaceuticals: Artificial intelligence in drug discovery and development, Skin Sensitisation Case Study, Prospects and challenges of multi-omics data integration in toxicology

5.3 CRISPR Screens for Drug Target Validation

Discovery: CRISPR/Cas9 gene editing and single-cell RNA sequencing enabled rapid identification and validation of drug targets, verifying AI-predicted targets for cancer and neurodegenerative diseases.
Validation: Accelerated the discovery of novel treatments by linking gene perturbations to therapeutic efficacy.
Impact: Reduced reliance on animal models for target validation.
References: CRISPR Cas9 Gene Editing, CRISPR-Cas9 in Functional Genomics: Implications for Target Validation in Precision Oncology, Target Validation with CRISPR, The future of pharmaceuticals: Artificial intelligence in drug discovery and development

5.4 AOP-Linked In Vitro Screens for Seizure Liability

Discovery: A government-industry collaboration mapped mechanisms leading to drug-induced seizures using adverse outcome pathways (AOPs) and in vitro assays.
Validation: Identified 27 biological target families linked to seizure mechanisms and developed 100+ assay endpoints.
Impact: Enabled systematic, mechanism-focused screening for pro-convulsant risk early in development. Replaces animal models which fail to predict drug-induced seizures.
References: De-risking seizure liability, Can New Approach Methodologies De-Risk Drug Development?, iPSC derived cardiomyocytes for cardiac toxicity assessment

6. Toxicology & Safety Assessment via NAMs

NAMs are transforming toxicology and safety assessment by providing human-relevant models for predicting compound toxicity, skin sensitization, endocrine disruption, and mixture toxicology. This section explores how regulatory agencies and industries are adopting these methods to improve chemical risk assessment and reduce reliance on animal testing.

6.1 Endocrine Disruption Assessment (Tox21 ER Model)

Discovery: The Tox21 ER pathway battery identified compounds interfering with human hormones using robot-based results.
Validation: EPA accepted this computational model as an alternative to rodent uterotrophic assays.
Impact: Provides an accepted non-animal alternative for testing in hazard identification for endocrine disruptors.
References: Toxic Alerts of Endocrine Disruption Revealed by Explainable Artificial Intelligence, Tox21: Chemical testing in the 21st century, Use of New Approach Methodologies

6.2 Skin Sensitization Hazard & Potency Prediction

Discovery: The OECD TG 497 “Defined Approaches” guideline combined multiple NAMs specifically Peptide reactivity assays (DPRA), Keratinocyte activation (KeratinoSens), Dendritic-cell activation (h-CLAT), and In silico models.
Validation: Correctly classified skin sensitization hazard and potency for chemicals, including those not previously tested in animals, with performance equal to or better than mouse assays.
Impact: Established a regulatory framework for animal-free safety testing of skin sensitizers.
References: Skin Sensitisation Case Study: Comparison of Defined Approaches including OECD 497 Guidance, Advancing Skin Sensitization Potency Categorization Using U-SENS™ in OECD TG 497, Standardisation and international adoption of defined approaches for skin sensitisation, Evaluating the ability of defined approaches to predict the human skin sensitisation potential of chemicals previously untested in new approach methodologies, Case Study on the Use of Integrated Approaches for Testing and Assessment for skin sensitisation

6.3 Bioactivity-Exposure Ratio (BER) for PFAS Risk Assessment

Discovery: For emerging PFAS compounds, regulators used in vitro assays to calculate human equivalent doses (HED) and derive a Bioactivity-Exposure Ratio (BER).
Validation: BER served as a protective surrogate in the absence of traditional animal data.
Impact: Enabled risk-based prioritization of chemicals based on biological perturbation likelihood.
References: S13-02 NAMs to investigate chemical-induced immunotoxicity: the cases of PFAS and BPA analogs, [Use of new approach methods (NAMs) in risk assessment](https://www.canada.ca/en/health-canada/services/chemical-substances/fact-she ets/use-new-approach-methods-risk-assessment.html), Sensitivity Analysis of the Inputs for Bioactivity-Exposure Ratio Calculations in a NAM-Based Systemic Safety Toolbox

6.4 Mixture Toxicology via NAMs

Discovery: NAM-based defined approaches (originally for individual substances) were extended to complex mixtures (e.g., pesticide formulations).
Validation: Demonstrated that panels of in chemico, in vitro, and in silico assays could identify and rank sensitization potential of formulations.
Impact: Advanced the understanding of combined exposure effects without animal testing.
References: iPSC derived cardiomyocytes for cardiac toxicity assessment, Case Study on the Use of Integrated Approaches for Testing and Assessment for skin sensitisation of Diethanolamine, Chemical testing using new approach methodologies

6.5 Reconstructed Human Skin Models Replace Animal Testing for Cosmetics and Chemicals

Discovery: Validated by OECD and regulatory agencies as replacements for the Draize rabbit skin irritation test.
Validation: Developed by MatTek (EpiDerm), Episkin (L’Oréal), Henkel, now standard in the EU and increasingly adopted globally.
Impact: Eliminates animal use for skin irritation/corrosion endpoints for cosmetics and many chemicals in accepting jurisdictions.
References: In Vitro Skin Models as Non-Animal Methods for Dermal Drug Development and Safety Assessment, Artificial Skin Models for Animal-Free Testing

6.6 Corneal and Eye Irritation Models

Discovery: Validated alternatives to the Draize rabbit eye test.
Validation: Developed by EpiOcular (MatTek), SkinEthic HCE (Episkin), assesses eye irritation potential of chemicals and consumer products.
Impact: Provides human-relevant models for eye irritation testing with validated non-animal alternatives.
References: Tissue Engineered Mini-Cornea Model for Eye Irritation Test, Corneal epithelium models for safety assessment in drug development: Present and future directions

7. Regulatory & Industry Adoption of NAMs

Regulatory agencies and pharmaceutical companies are increasingly embracing NAMs to streamline drug development, enhance predictivity, and align with ethical and scientific advancements. This section examines key milestones—such as the FDA Modernization Act 2.0 and OECD standards—that are paving the way for the global adoption of human-relevant, animal-free methodologies in biomedical research.

7.1 FDA Modernization Act 2.0

Discovery: The FDA Modernization Act 2.0 (2022) removed the federal mandate for animal testing in new drug applications.
Validation: A significant move by FDA to move away from using the animal model.
Impact: Explicitly encouraged the use of NAMs (in vitro, in silico) in preclinical safety assessments.
References: FDA Modernization Act 2.0: transitioning beyond animal models with human cells, organoids, and AI/ML-based approaches, How new approach methodologies are reshaping drug discovery, Organ-on-a-chip meets artificial intelligence in drug evaluation

7.2 FDA CDER NAM Validation Guidance (March 2026)

Discovery: FDA’s Center for Drug Evaluation and Research (CDER) released draft guidance establishing a validation framework for NAM-derived data.
Validation: Based on scientific confidence, human biological relevance, and “fit-for-purpose” utility, these guidelines are a significant move away from using the animal model.
Impact: Provided a clear regulatory pathway for integrating NAMs into Investigational New Drug (IND) applications.
References: FDA Releases Draft Guidance on Alternatives to Animal Testing in Drug Development, New Approach Methodologies (NAMs) in Drug Development

7.3 OECD International Standards for NAMs

Discovery: The OECD Guidance Document 34 established international standards for the validation and acceptance of alternative test methods.
Impact: Facilitated global harmonization and adoption of NAMs in regulatory frameworks.
References: List of Alternative Test Methods and Strategies (or New Approach Methodologies NAMs), OECD Series On Testing And Assessment Number 34

7.4 Industry Investments in NAMs

Discovery: Major pharmaceutical companies (e.g., Roche, Johnson & Johnson, AstraZeneca) invested in NAMs: Emulate organ-on-a-chip platforms for toxicity prediction, Organoids and computational modeling for personalized medicine.
Validation: Business interests confirm the efficacy of NAMs.
Impact: Accelerated the transition toward human-relevant models in drug development.
References: How new approach methodologies are reshaping drug discovery

7.5 Tebentafusp (Kimmtrak) Regulatory Approval

Discovery: Tebentafusp (Kimmtrak) became the first immunotherapy to reach clinical trials and regulatory approval without in vivo animal pharmacodynamic data.
Validation: Because the drug lacked activity in any animal species, the sponsors relied entirely on human-centric NAMs to justify safety and efficacy for its IND submission.
Impact: Establishes a major regulatory milestone proving that human-relevant data can fully replace animal testing in specific contexts for first-in-class therapeutics.
References: Immunocore announces FDA approval of KIMMTRAK® (tebentafusp-tebn) for the treatment of unresectable or metastatic uveal melanoma, Summary Basis of Decision for Kimmtrak in Canada

7.6 Aspect Biosystems — 3D Bioprinting Platform

Discovery: Developing bioprinted human tissue models as alternatives to animal testing, representing Canadian innovation in NAMs.
Validation: Bioprinted Tissue Therapeutics designed to replace biological function in the body.
Impact: Provides advanced tissue models for drug development.
References: Aspect Biosystems

7.7 Canadian Centre for Alternatives to Animal Methods (CCAAM)

Discovery: Canada’s first dedicated academic center for NAM research, conducted and promoted research using human-relevant, non-animal approaches.
Validation: Established in 2017 at the University of Windsor, Ontario.
Impact: Advances NAMs adoption in Canada.
References: CCAAM

7.8 USP Chapter <86> Recombinant Reagents for Endotoxin Testing

Discovery: The U.S. Pharmacopeia (USP) officially implemented Chapter <86> in May 2025, endorsing the use of non-animal-derived reagents for bacterial endotoxin testing.
Validation: The chapter allows the use of recombinant Factor C (rFC) and recombinant cascade (rCR) reagents, which utilize endpoint fluorescence and chromogenic techniques derived from gene sequences of the horseshoe crab.
Impact: Modernizes quality control in pharmaceutical manufacturing, potentially saving up to 90,000 animals per year while increasing batch-to-batch consistency.
References: <86> Bacterial Endotoxins Test Using Recombinant Reagents

Summary Table: Key NAM-Enabled Discoveries

Thematic Area	Discovery	Validation Status
AI-Driven Discovery	AI-designed drug for idiopathic pulmonary fibrosis (Insilico Medicine)	Phase II clinical trials
	AI repurposing of baricitinib for COVID-19	Clinical validation
	Topiramate identified for IBD via transcriptomic analysis	Preclinical/clinical studies
Organ-on-a-Chip	Liver-on-a-chip identifies hepatotoxicity in 87% of drugs missed by animal models	In vitro, regulatory acceptance
	Lung-on-a-chip for antiviral efficacy and tumor heterogeneity	In vitro, preclinical validation
	ALS Pathogenesis and Early Biomarkers	Multi-omics validation
	Cervical Protective Role in Dysbiosis	In vitro validation
Human Organoids	FIS assay for cystic fibrosis: personalized drug response prediction	Clinical implementation
	Patient-derived organoids for gene therapy in DMD	Preclinical validation
	OPTIC trial: 83.3% accuracy in predicting mCRC treatment response	Clinical validation
	Miller-Dieker Syndrome (MDS) Root Cause	Time-lapse imaging validation
	IGF-1 Dependency in Lung Cancer Subtypes	Genetic ablation validation
	Kidney assembloids for PKD modeling	In vitro validation
In Silico Modeling	PBPK modeling for drug safety and PK/PD predictions	FDA-accepted for submissions
High-Throughput & Omics	Tox21: 18-assay ER pathway battery for endocrine disruption	Regulatory acceptance (EPA)
	Multi-omics for toxicity pathway discovery	Peer-reviewed validation
Toxicology & Safety	OECD TG 497: Defined approaches for skin sensitization	Regulatory framework
	BER for PFAS risk assessment	Regulatory adoption
Regulatory Adoption	FDA Modernization Act 2.0: End of animal testing mandate in drug development	Legislative implementation
	FDA CDER NAM Validation Guidance (March 2026)	Draft guidance issued
	Tebentafusp (Kimmtrak) Regulatory Approval	Regulatory milestone

Conclusion: The NAMs Revolution in Biomedical Research

NAMs are not merely replacements for animal tests—they represent a fundamental transformation in scientific understanding and drug development. By leveraging human biology, robotics, AI, and computational modeling, NAMs offer:

Greater predictive accuracy for human responses.
Faster, cheaper, and more ethical research.
Personalized medicine through patient-specific models (organoids, organ-on-a-chip).
Regulatory acceptance and industry adoption.

The discoveries highlighted in this report demonstrate that NAMs are already delivering validated medical breakthroughs, from AI-designed drugs to organoid-based therapies and in silico clinical trials. As these technologies mature, they will redefine the future of biomedical research and patient care.

Suggested next steps for innovators:

Explore specific NAM platforms (e.g., Emulate, Insilico Medicine) for your research or project needs.
Investigate regulatory pathways for integrating NAMs into your workflow. See notebooklm whitepaper Strategic Framework for Navigating the Regulatory Transition to New Approach Methodologies (NAMs)
Consider collaborations with industry leaders in organ-on-a-chip or AI-driven drug discovery.

Disruptive Technologies

Mon, 28 Feb 2022 19:51:46 -0800

We present various aspects of technology that will disrupt the status quo. Last Updated: <2022-02-28 Mon>

Introduction

This is the disruptive technology (distec) collection that we have been investigating since the end of March 2021.

We came across distec after a presentation on Beyond Animal by James Arbib of Rethinkx and were very impressed not only by the concept, but also by what is inevitably on the way. One of the main benefits of distec is to annihilate existing industries that are detrimental to lifeforms and environment. Many of the presenters in the videos section talk not only about the technology, but also about the importance of the ethical result.

We have long maintained that the achievement of animal rights (which is the fundamental ethic that present day science can determine via sentience criteria), will occur as a result of two forces, legal and business. The latter is happening through distec.

This page will be updated as we study this venture and examine investment opportunities.

RethinkX

“RethinkX is an independent think tank that analyzes and forecasts the speed and scale of technology-driven disruption and its implications across society. We produce impartial, data-driven analyses that identify pivotal choices to be made by investors, business, policy and civic leaders.”

their mission is to “facilitate a robust global conversation about the threats and opportunities of technology-driven disruptions, and highlight choices that could lead to a more equitable, healthy, resilient and stable society.”

the site is primarily sectioned into

About

About rethinkx

an independent think tank that analyzes and forecasts the speed and scale of technology-driven disruption and its implications across society

Meet the team

Tony Seba, Founder is a world-renowned thought leader, Silicon Valley entrepreneur, educator and author
James Arbib, Founder is a London-based investor in technology
Uzair Niazi, Founding Director has over 20 years of high-tech industry experience leading product development teams across the globe
Adam Dorr, Research Fellow is an environmental social scientist and technology theorist
Bradd Libby, Research Fellow responsible for our complex systems analysis and modelling
Taylor Hinds, Research Associate provides support on various projects, with a special focus on disruption within the agriculture sector
Richard Anderson, Editorial Adviser a journalist and editor for more than 20 years

Getting it right

The Seba Technology Disruption Framework takes a systems approach to analyze the market forces triggered by technology convergence, business model innovation, product innovation, and exponential improvements in both cost and capabilities. It captures the complex processes that drive a pattern of rapid, non- linear change.

Blog

The Impact of Covid-19 on Food – Part 1: The Collapse of the Old
The Impact of Covid-19 on Food – Part 2: The Rise of the New
The power of disruption: Winners take it all
Precision fermentation is nothing new and it’s here to stay
Precision Fermentation: What exactly is it?
Precision Fermentation and the Disruption of the Palm Oil Industry
Take a Byte! Food-as-Software
Precision Regulation – Policy as a key shaper of the new food system
The Social License
Why would you build a million-mile car?
and more …

Reports

LCOE levelized cost of electricity

is a measure of the average net present cost of electricity generation for a plant over its lifetime
represents the average revenue per unit of electricity generated that would be required to recover the costs of building and operating a generating plant during an assumed financial life and duty cycle

LCOE is (sum of costs) / (sum of energy produced) calculated as follows:

$$ LCOE = \frac {\sum_{t=1}^{n} \frac{I_t+M_t+F_t}{(1+r)^t}} {\sum_{t=1}^{n} \frac{E_t}{(1+r)^t}} $$

Symbol	Explanation
$@I_t$@	investment expenditures in the year t
$@M_t$@	operations and maintenance expenditures in the year t
$@F_t$@	fuel expenditures in the year t
$@E_t$@	electrical energy generated in the year t
$@r$@	discount rate
$@n$@	expected lifetime of system or power station

The Great Stranding

How Inaccurate Mainstream LCOE Estimates are Creating a Trillion-Dollar Bubble in Conventional Energy Assets.

Executive Summary

A large and rapidly-expanding global financial bubble now exists around conventional coal, gas, nuclear, and hydro power energy assets. This bubble has in part been created by mainstream energy analyses that have, for the last decade, significantly underestimated the levelized cost of electricity (LCOE) from conventional power plants because they assume these plants will be able to successfully sell the same quantity of electricity each year from now through 2040 and beyond. This assumption has been false for at least ten years.
- rates at which conventional power plants are utilized will continue to decrease
- conventional energy asset valuations are heavily overstated
- critical error: they assume high and constant capacity factor for 20y lifetime
- sources that commit this error include …
- capacity factor in conventional energy has been dropping since at least 2010
- false assumptions have made conventional energy assets appear more attractive than they actually are
- financial bubble is investment in an asset class above what the fundamental value can return
- SWB will drive capacity factor of coal, gas, nuclear, and hydro power plants toward zero
Our analysis has a number of important implications for energy and finance, as well as for society and the environment at large.
Rethinking LCOE through lens of disruption

Underestimation of coal, gas, and nuclear power plant LCOE strongly biases cost comparisons with SWB and other technologies in favor of these incumbents … calculation of LCOE itself presumes that a power plant will obtain sufficient revenues and cashflows to cover costs

In competitive markets, neither the assumption that capacity factor will remain high and constant nor the assumption that electricity can be successfully sold at higher prices holds true.
- coal
  - size of the coal fleet has shrunk dramatically over the last decade in both the United States (47% decline) and the United Kingdom (79% decline)
  - there’s not a single regulated coal power plant that is competitive in the U.S. today
  - historical data show high and constant capacity factor has been invalid for over a decade
  - coal index fell 99% since 2011 and was discontinued by S&P Global
  - coal cost/kwh forecast are unfeasible compared to SWB
  - corrected LCOE for coal power is far higher than reported
  - by 2030, the LCOE of a new coal power plant is nearly 9 times greater than the U.S. EIA Reference Case assumption
- gas
  - U.S. EIA has assumed a constant capacity factor of 87% for the entire 20-year technical life of new gas power plants causing LCOE to be artificially lowered
  - corrected LCOE of new builds rises as average capacity factor continues to decline
- nuclear
  - LCOE of nuclear is much higher than mainstream analysts claim, when costs such as decommissioning and full insurance costs are accounted
  - nuclear power plants entering service in 2020 have an LCOE of 22.5 cents per kilowatt-hour – 175% greater the U.S. EIA’s current estimate of 8.2 cents per kilowatt-hour
- hydro
  - analysts assume a constant capacity factor throughout the lifetime of any newly-built facility
  - corrected LCOE of a new hydro power plant is nearly 10 times greater than the U.S. EIA Reference Case assumption
all scenarios presented are for illustrative purposes, but more realistic outcomes is full disruption to collapse … so it’s gonna be worse than it looks!
Implications

analysis has a number of important implications for energy and finance, as well as for society and the environment at large:
- Conventional energy assets are severely mispriced due to false assumptions, creating a bubble
- Coal, gas, nuclear, and hydro power are no longer competitive, SWB will capture increasing share
- Solar and wind power reached cost parity and became cheaper sooner than expected (1/20th)
- SWB disruption will proceed faster than expected
- Coal and gas power plants with integrated CCS are overvalued creating false narratives
- Governments must protect people, not industries, from the financial risk
- Carbon neutrality can be achieved more quickly and cheaply than generally expected
serious choices to make knowing the above implications.
Choices

leaders should choose to reject conventional dogma and instead demand that all energy assets – from plants and refineries to pipelines and ports – adopt a dynamic and transparent LCOE model that more realistically reflects current as well as likely future market conditions and risks based on the reality of the SWB disruption.
- dynamic LCOE choices:
  - use a dynamic LCOE model in their cash flow calculations
  - assume new power plants begin operation with only the market capacity factor
  - power plant operational lifetimes should also reflect the disruption by SWB
  - accounting authorities should allow for faster depreciation schedules
- market LCOE choices:
  - Demand analysts calculate LCOE on the basis of realistic assumptions for capacity factor
  - Demand that conventional energy promoters calculate LCOE by realistic assumptions
  - Review asset valuations of existing holdings of conventional energy assets realistically
  - Lend to conventional energy asset owners on the basis of realistic LCOE calculations
  - Valuation of supply chain assets should take into account a realistic demand model
  - Government regulators should not enlist ratepayers to subsidize
  - Utilities be obligated to use shareholder capital in any new conventional energy investment
- savings LCOE choices:
  - Financial institutions should not use the public money to invest in conventional energy assets
  - Asset managers should not invest in conventional energy assets or their supply chains
  - Market openness/transparency/liquidity should be requisite conditions for pension investment
  - asset managers should not lend to conventional energy asset owners
not adopting the above choices could lead to disruption of societal existence as severe as the disruption awaiting conventional industries.
Death Spiral

The disruption of the electric power sector by solar, wind, and batteries (SWB) during the 2020s will unfold much more rapidly than mainstream forecasts.

SWB will enjoy a virtuous cycle of accelerating adoption while incumbent technologies enter a death spiral.

the virtuous cycle for SWB
- falling costs, which increases demand
- demand drives industry growth, attracts investment, increases government support, leading to an expansion of supply
- supply expansion improves capabilities, lower costs further, increases acceptance and more demand
new technologies also bring social and environmental benefits over a conventional coal, gas, and nuclear technologies.

the vicious cycle for conventional
- falling demand as they are progressively outcompeted by SWB
- less demand means less revenue, profit, investment, government support, and therefore less supply
- supply reduction result in rising costs and downward demand
The virtuous cycle enjoyed by SWB and the vicious cycle suffered by coal, gas, nuclear, and hydro power will feed into each other, because falling demand for the old and growing demand for the new serve to accelerate one another.

Rethinking Energy 2020-2030

100% Solar, Wind, and Batteries is Just the Beginning.

We are on the cusp of the fastest, deepest, most profound disruption of the energy sector in over a century. Like most disruptions, this one is being driven by the convergence of several key technologies whose costs and capabilities have been improving on consistent and predictable trajectories – namely, solar photovoltaic power, wind power, and lithium-ion battery energy storage. Our analysis shows that 100% clean electricity from the combination of solar, wind, and batteries (SWB) is both physically possible and economically affordable across the entire continental United States as well as the overwhelming majority of other populated regions of the world by 2030. Adoption of SWB is growing exponentially worldwide and disruption is now inevitable because by 2030 they will offer the cheapest electricity option for most regions. Coal, gas, and nuclear power assets will become stranded during the 2020s, and no new investment in these technologies is rational from this point forward.

Rethinking Food and Agriculture 2020-2030

The Second Domestication of Plants and Animals, the Disruption of the Cow, and the Collapse of Industrial Livestock Farming.

By 2030, the number of cows in the U.S. will have fallen by 50% and the cattle farming industry will be all but bankrupt. All other livestock industries will suffer a similar fate, while the knock-on effects for crop farmers and businesses throughout the value chain will be severe. Rethinking Food and Agriculture shows how the modern food disruption, made possible by rapid advances in precision biology and an entirely new model of production we call Food-as-Software, will have profound implications not just for the industrial agriculture industry, but for the wider economy, society, and the environment.

Rethinking Transportation 2020-2030

The Disruption of Transportation and the Collapse of the Internal-Combustion Vehicle and Oil Industries.

By 2030, within 10 years of regulatory approval of Autonomous Vehicles (AVs), 95 percent of U.S. passenger miles traveled will be served by on-demand autonomous electric vehicles owned by fleets, not individuals, in a new business model we call “transport-as-a-service” (TaaS). Rethinking Transportation shows how TaaS disruption will have enormous implications across the transportation and oil industries, decimating entire portions of their value chains, causing oil demand and prices to plummet, and destroying trillions in investor value — but also creating trillions in new business opportunities, consumer surplus and GDP growth.

Rethinking Humanity

During the 2020s, key technologies will converge to completely disrupt the five foundational sectors that underpin the global economy, and with them every major industry in the world today.

In information, energy, food, transportation, and materials, costs will fall by a 10x or more, while production processes an order of magnitude more efficient will use 90% fewer natural resources with 10x-100x less waste. The knock-on effects for society will be as profound as the extraordinary possibilities that emerge. For the first time in history, we could overcome poverty easily. Access to all our basic needs could become a fundamental human right. But this is just one future outcome. The alternative could see our civilization collapse into a new dark age. Which path we take depends on the choices we make, starting today. The stakes could not be higher.

Seba Technology Disruption Framework

RethinkX uses the Seba Technology Disruption Framework™ to help analyze and model the disruptions we study.

Developed by Tony Seba, this framework is the result of more than a dozen years of research and teaching on technology disruptions, business model innovation, finance and strategic marketing of high-tech products and innovations at Stanford Continuing Studies, and has been used to understand and anticipate disruptions in several industries.

notes:

illustrates the framework mechanism through diagrams
convergence of technologies -> exponential growth -> disruption

Resources

Guidance for Decision Makers and Investors

this is the action plan from rethink humanity

Policy Makers

a policy factsheet for autonomous, electric, on-demand vehicles
a policy primer for the coming transportation disruption

Businesses and Investors

factsheet on autonomous vehicles and end of individual car ownership
business and investor primer for coming transportation disruption

Videos

Various videos on youtube some of which relate to the reports.

Rethinking Energy 2020-2030: 100% Solar, Wind, and Batteries is Just the Beginning

The Great Stranding: How Inaccurate Mainstream LCOE Estimates are Creating a Trillion-Dollar Bubble

Rethinking Humanity: An extraordinary interview with American futurist Tony Seba of RethinkX

Spread The Sun A New Era: featuring Tony Seba RethinkX; Frédéric Storck CNR; Anis Jouni CEA-INES

The Great Collapse: Are YOU Prepared? Investing in Disruption Starts With Understanding It

Ark-Invest

Investment Solutions

area	arkF	arkG	arkK	arkQ	arkW	arkX	TOTALS
3D Printing			1	1		1	3
Aerial Drones				1		1	2
Ag Bio		1					1
Artificial Intelligence	1		1		1		3
Autonomous Technology				1	1		2
Autonomous Vehicles			1	1			2
Biotech		1					1
Cloud Computing					1		1
DNA Sequencing		1	1				2
Digital Media					1		1
Digital Wallets	1						1
ECommerce	1						1
Enabling Technology						1	1
Fintech	1		1				2
Gene Editing		1					1
Gene Therapy		1					1
IoT					1		1
Lending	1						1
MaaS				1			1
Mobile Payments	1				1		2
Molecular Diagnostics		1					1
Orbital(sub) Aerospace						2	2
Reusable Rockets						1	1
Risk Transformation	1						1
Robotics			1	1			2
Targeted Therapeutics		1					1

By Product Type

Why Innovation

Invest In The Future Today

Innovation should displace industry incumbents, increase efficiencies, and gain majority market share.
Innovation Must Meet Three Criteria
- Experience dramatic cost declines and unleash waves of incremental demand (wright’s law: $Y = a X^b$)
- Cut across sectors and geographies
- Serve as a platform for additional innovations
Major Innovation Platforms
- Artificial Intelligence
- Energy Storage
- Robotics
- DNA Sequencing
- Blockchain Technology

Take Advantage of Four Market Inefficiencies

The Market’s Short-Term Time Horizon
- long flat adoption curves
- performance declines before mass market acceptance
- accelerated growth results in winner take all
The Silo-ization of Wall Street
- cross-sector disruptive innovation themes to capitalize on the convergence of research
The Passive Public Markets
- innovative public companies with forward looking growth are most inefficiently priced part of market
The Closed-Off Research and Investment Mentality
- an Open Research Ecosystem that combines top-down and bottom-up research
thematic investment process
- top-down bottom-up
  1. insights between the portfolio manager, director of research, analysts, external sources
  2. analysts are organized by cross-sector innovation themes
  3. identify entry points for tech-enabled disruption
  4. creates investment briefs and valuation models
  5. proprietary scoring system to evaluate stocks
  6. company scores are discussed weekly
- scoring metrics
  1. company people culture
  2. execution
  3. moat
  4. product leadership
  5. valuation
  6. thesis risk

Make The World A Better Place

sustainable investing
sdg
how?
1. Next Generation Internet
2. DNA Sequencing
3. Fintech
4. Robotics & Autonomous Technology

About ARK

The ARK Difference

invest at the pace of innovation
1. Sole Focus on Disruptive Innovation
2. Experienced Investment Leadership
3. Thematic Analysts Organized by Innovation
4. Transparent and Open Research Ecosystem
5. Long-Term Investment Time Horizon

Investment Process

A. top-down

Ideation examines from the top-down how the world is changing and where it is headed
Sizing The Opportunity models cost-curves and calculates elasticity of demand to identify entry points

bottom-up
1. Stock Selection And Valuation valuation and revenue model for each company in the portfolio over the next five years
2. Portfolio And Risk Management monitors the underlying investment thesis of every company weekly
open research ecosystem collaborate within particular themes, as well as across themes
incorporates Sustainability Intrinsically investment philosophy and process inherently considers ESG principles that align with SDG

Our Team

Work at ARK

Press & Media

Board of Directors

Corporate Responsibility

ARK believes that innovation is key to growth and will make the world a better place. We seek to invest in companies aligned with this belief, but also to operate our own company in a way that enhances society. To succeed in this mission, ARK implements responsible corporate governance, fosters a diverse and inclusive workforce, and gives back to organizations that we believe are promoting good health and well-being, quality education, and gender equality.

ARK Swag Store

FAQ

Active Research Management
ARK researches across sectors, industries, and markets to gain a deeper understanding of the convergence and market potential of disruptive innovations.
ARK’s Open Research Ecosystem seeks to capitalize on rapid change through an open approach and the convergence of insights.
ARK actively engages with Theme Developers as part of our research ecosystem.
Thematic investing seeks to capitalize on long-term trends that cut across economic sectors and geographic boundaries.
While benchmarks reflect past successes, thematic investing seeks to capture future growth allowing investors to earn a market premium.
We research and invest in a wide range of companies, from mega caps to micro caps that we believe are going to contribute to and benefit from the rapidly changing market landscape.
ARK’s cross-sector portfolios aim to uncover disruptive innovation that impacts multiple industries.
As a result of extensive and iterative research steps, ARK anticipates and quantifies multi-year value-chain transformations and market opportunities.
ARK will sell a company if it believes that a disruptor has become disrupted itself, or that it is no longer on the leading edge of fast-moving industries or innovation.
In fast-moving themes, like those of our strategies, volatility is the foundation of opportunity and potentially higher returns.
ARK believes the companies it invests in will be prominent in such indices over a full market cycle
recognize the misunderstood nature of many companies’ fundamentals and look to identify companies that are leaders rather than the largest market capitalization company in a passive index
If a stock’s share price has fallen in the market due to short-term controversy, ARK tends to increase its position (providing the thesis is unchanged). If a stock is overhyped, ARK will trim the position to take profits.
ARK suggests a long-term investment horizon of a full investment cycle, or 7+ years.
artificial intelligence, DNA sequencing, robotics, energy storage, and blockchain technology are the innovation platforms leading the global economy into what could be the most transformative period in history

Research Center

Videos

Big Ideas 2022: Summit

Big Ideas 2021: Cathie Wood and Brett Winton

Ark Invest Big Ideas 2021: Cathie Wood Explains (Full Interview)

ARK: The five platforms of disruptive innovation (an excellent Cathie Wood interview)

Ticker Symbol: YOU

An exceptionally good channel by applied math grad Alex! He follows and explains the Ark-Invest moves which can help in making trading decisions.

Nanalyze

A website with articles on a wide range of disruptive technology topics and a focus on investing.

Some articles of administrative interest:

Investing in Emerging and Disruptive Technologies provides an indication of what to expect on the site
The Nanalyze Disruptive Tech Investing Methodology explains their picking process
Calculating Our Nanalyze Tech Stock Portfolio Performance shows their results from 1998 at 480%

Below are specific areas of investment (found in the disruptive technologies dropdown menu) that are of interest to us:

3D Printing

What is 3D Printing?

the construction of three-dimensional objects from Computer-Aided Design (CAD) models or other digital 3D design models

3D Printing Materials and Technology
- plastics, metals, ceramics, concrete, paper, and even certain kinds of foodstuffs
- stereolithography (SLA), Material jetting, powder bed fusion
3D Printing Metals
- many ways to go about 3D printing metal (eg joule printing)

The Industrial 3D Printer

focus areas have emerged in various industries

Healthcare

3D Printing and Dentistry
- straighten teeth at home
3D Printing Medical Devices
- instrumentation, implants, prostheses, drug delivery
3D Bioprinting
- print organs on demand

Manufacturing

largely found its place in prototyping for aerospace, shoes, eyeware, alternative proteins

On-Demand Manufacturing
- additive and subtractive for custom parts
3D Printing and Distributed Manufacturing
- printers are connected into a giant network

Buyer Beware

ignore the glossy investor decks and dig into the SEC filings to find all the broken promises made over the years
When 3D printing hit peak popularity in the investment community, the over-the-counter roaches started coming out of the woodwork

3D Printing Penny Stocks
- everyone should know to stay far clear of all over-the-counter (OTC) stocks and penny stocks
3D Printing Stocks That Need Revenues
- Perhaps some of the most blatant incompetency was seen on crowdfunding platforms like Kickstarter. While companies like Formlabs ran successful crowdfunding campaigns to pre-sell their printers, most projects over-promised and under-delivered.

3D Printing Startups

Venture capitalists have been pouring money into 3D printing startups

Three 3D Printing Unicorns
- the most exciting are the mythical unicorns
- value based on a variety of factors, rarity being one

3D Printing Stocks and ETFs

there is no designated industry classification for 3D printing stocks
investigate each company that claims to be involved in 3D printing to make sure they’re not a 3D printing pretender
If you invested in 3D printing stocks at peak hype, you would have lost a lot of money

Artificial Intelligence

artificial intelligence is an emerging technology with the potential to transform every company in every industry in just about every way you can imagine

What is Artificial Intelligence?

see An Artificial Intelligence Definition for Beginners

AI Chips
- specialized chips uses to train machine algorithms (training chips) and then the chips they run on in production (inference chips)
- industry is now moving towards chips that are highly customized with software that’s been optimized for specific tasks
Not Everything is Artificial Intelligence
- these stocks have come down to earth making everyone realize not everything is artificial intelligence
- even if you are using artificial intelligence, your company can still underperform the stock market
Artificial Intelligence and Transparency
- they’ve now decided that artificial intelligence tells the truth too much, and should be silenced
- kowtow to their demands under the guise of representing some class of people
- Always look at what’s motivating people who call for AI transparency

How Does Artificial Intelligence Use Big Data?

What proprietary data sets are you using to train your algorithms with such that you’ll be able to realize a competitive advantage?

Big Data vs. Data Warehouses
- big data lets us find “the unknown unknowns” things we didn’t even think of to start measuring
Unstructured Data and Data Privacy
- Everything that gets publicly posted on the Internet, anywhere, is unstructured data that’s probably being used right now by AI algorithms to glean some insights from.

Examples of Artificial Intelligence Use Cases

over 3,500 startups using artificial intelligence to do just about anything you can think of
Many artificial intelligence startups are seeing success by targeting large industry verticals

AI in Sales and Marketing
- you’re selling online or from a brick-and-mortar outlet, there are many ways AI can help
AI in Human Resources
- not big fans of human resources (HR) because they largely get in the way while trying to create more work for everyone
AI for Recruiting
- we speculated that competent tech startups will start to deliver effective AI solutions, and all these “boutique” recruitment firms (where the only qualification to start one is that you can fog a mirror) will start to lose out on all those exorbitant recruiting fees they were raking in to find tech people
- Any business that proposes we change this model and start rewarding people based on anything but competence needs to be condemned from the highest pulpit
AI for Cybersecurity
- cybersecurity is a high-growth sector which investors are pouring money into. That’s because hackers – 90% of whom are financially motivated – are becoming increasingly sophisticated in their attacks.
- AI is being used in many creative ways to thwart cybercrime. Speaking of creativity, AI can do that too.
AI Algorithms Get Artistic
- also being used for more creative applications
AI for Everything
- decided to deep dive into a few domains where artificial intelligence is excelling right now at solving big problems

Natural Language Processing and Speech Recognition

methods which AI algorithms use to understand human speech in written, verbal, and non-verbal forms
natural language processing includes everything from algorithms that write news articles to interpreting sign language for the deaf using computer vision
Investing in Natural Language Processing

Artificial Intelligence for Healthcare

industry which is being transformed the most by artificial intelligence right now is healthcare
Investing in AI Healthcare Companies and Stocks

Artificial Intelligence for Computer Vision

a field of research for designing machines with the ability to process, understand, and use visual data just as humans do (dominated by large chinese startups)
Investing in Computer Vision Companies and Stocks

Global Artificial Intelligence

there’s a global AI race taking place where every country is competing to build the best AI algorithms
The Global AI Race – Top AI Startups Around the World

Will AI Replace My Job?

probably

Robotic Process Automation or RPA
- robotic process automation (RPA) is when we teach machine learning algorithms how to do white-collar jobs that have a certain element of predictability to them

Investing in AI Stocks

The best question to ask a company that claims they’re “doing AI” is what proprietary datasets do they have to train their algorithms that nobody else has?
How to Invest in AI Stocks in 2021

Augmented and Virtual Reality

the promise of merging the digital with the real world in different aspects of our lives is a long way off from materializing
relative immaturity of the market means there are fewer opportunities for the retail investor

What is the Difference Between Augmented Reality and Virtual Reality?

Virtual reality is a completely digital environment that you are immersed in.
Augmented reality is where your view of reality is “augmented” with digital additions.
In mixed reality, digital objects appear within the natural world.

AR/VR Hardware

VR has labored to find a widespread consumer audience willing to invest in what is still a somewhat awkward technology with limited content
The smart money is generally headed into business solutions.

AR/VR Headsets
- There are a few recognizable names among the many augmented and mixed reality headset manufacturers.
AR/VR Headset Suppliers
- Not every player in the AR/VR headset space is a finished goods manufacturer.
AR/VR Hardware Accessories
- There are plenty of startups developing technology to help VR users feel with all five senses

VR Content

Content may be king, but virtual reality content hasn’t really risen far from jester status yet.
many item available though questionable at this stage

AR/VR for Enterprise Applications

while we’re waiting for AR/VR to catch on with consumers, the business world is quietly embracing the technology as a collaboration tool, especially with the ability to view and even manipulate data in three dimensions

Virtual Collaboration
- There’s nothing virtual about the payoff: Augmented reality businesses claim they can cut tasks like troubleshooting by more than half, often eliminating the cost of sending a technician on a site visit
Construction
- There are some pretty obvious VR applications across architecture, construction, and engineering. What better way to show someone how a space will look without the space actually being built?
- VR companies also hope to change the construction industry by offering skills training for construction workers
Healthcare
- The connection between AR/VR and healthcare may seem less obvious, but the business cases are at least as good as the ones we just discussed.
- the use cases for AR in healthcare are pretty robust
- wearables with some AR/VR-type tech are helping the blind to see using various vision-enhancement devices. In fact, technology for the blind could be worth billions, as the big R&D brains out there figure out ways to help the sightless see again
Retail
- For some, technology is only really valuable if it can help you sell stuff that people probably don’t need

Investing in AR/VR Stocks

Which, if any, of these companies should you target in your portfolio? Frankly, it’s a crapshoot, with the odds definitely in favor of the house.

Computing

When we talk about computing as an investment thesis, we need to think well beyond buying the picks and shovels.
a few examples of startups that are doing some very innovative things in the world of computing
there are lots of disruptive applications for computing that are left to be realized by ambitious entrepreneurs who are backed by visionary investors

Investing in Quantum Computing

What is Quantum Computing?
What Can We do With Quantum Computing?
Quantum Computing Companies
- Unfortunately for retail investors, largely all of the investing activities taking place for quantum computing are in privately held companies
- For retail investors, there’s one pure-play quantum computing stock worth taking a look at

Investing in 5G

What is 5G and Why is it Such a Big Deal?
- will enable autonomous cars to operate, connect trillions of devices and eventually turn your own handheld computer into a supercomputer, because all of the heavy processing can be done remotely
- everything on the planet will soon be connected to the cloud and the applications are limitless
5G Stocks

Investing in Cybersecurity

An entire industry has formed around those who want to do malicious things to earn a living
there are also many cybersecurity stocks for retail investors including ETFs

Authentication and Biometrics
- When it comes to authentication, there are many different methods that are appropriate for a variety of use cases.

Investing in Blockchain Technology

What is The Blockchain?
- blockchain is a ledger that records ownership and changes over time
Cryptocurrencies
- blockchain technology can be used to create currencies
Examples of Blockchain Use Cases
- The blockchain world is long on ideas and short on traction
- blockchain is the perfect solution for cross-border payments, and financial services applications in general
- enabling the world’s supply chains with blockchain to rid them of inefficiencies
Some Blockchain ETFs
- That’s because blockchain is far too new a technology for there to be many pure-play stocks for retail investors

Advances in Software Development

The companies that build the best software and wield the best datasets will have a sustainable competitive advantage which adds value over time
low-code or even no-code technologies that can turn just about anyone into a citizen developer
Eventually, we’ll build software so well that we won’t need customer support.

Investing in Disruptive Computing Stocks

The most exciting computing themes like quantum computing aren’t really investable yet for retail investors.
Various computing platforms will continue to service various use cases.

Fintech

Top fintech companies are enjoying success because they are solving pain points found in the traditional bank, a place where financial technology isn’t seen as a competitive differentiator.
Free trading seems to be the norm now, and they even have free trading for algo traders.
Some areas of fintech are more mature than others
motif, alpaca and others are interesting brokerages

Investing With Alternative Data

alternative data is often used by traders to generate alpha
For retail investors, there are ways to invest with fintechs that use alternative data to generate insights and increase returns across various alternative asset classes.

Investing in Alternative Asset Classes

things to invest in that may have been historically off-limits unless you were an ultra-high-net-worth individual

The Many Types of Fintech

Legaltech
- that search is to find the gems that can be used to sway a decision one way or another
- startups are finding that technology such as machine learning can come in handy for lawyers
Regtech
- RegTech is helping financial institutions make a healthier lunch
- Another area of regtech seeing lots of interest from investors is digital identity verification.
Insurtech
- accurately predict outcomes in order to make insurance policies profitable

The Biggest Fintech Company in the World

Ant Financial which has taken in $22 billion in funding and is now worth – at least the last time we checked – more than Goldman Sachs and Barclays combined, with a valuation of $150 billion

Fintech Investing and Stocks for Retail Investors

opportunities for retail investors aren’t so much in buying “fintech stocks” per se, but rather using the various fintech platforms to open up new avenues for investing in alternative asset classes, saving money using free personal finance apps

Venture Capital and Fintech
- some people have raised questions around how venture capital itself can be transformed
- For retail investors, you can buy shares of the world’s biggest startups on secondary markets
- For non accredited investors, there are some publicly traded venture capital firms.
Penny Stocks Suck
- There is one sure way to lose money investing in stocks, and that is by dabbling in penny stocks or what they call over-the-counter stocks.

Green Technology

What Are Green Technologies

The term “green technology” simply refers to ways in which we can use technology to make the world a better place.
It’s a global problem, and every country needs to address it differently.
Regardless of where you sit on climate change, we’re all better served if we clean up the planet.
The problems we need to solve with green technology also provide an opportunity for investors to make profits.

Renewable Energy Stocks and Companies

It’s not all about solar and wind power. Rain, tides, waves, geothermal heat, and biofuels, are all considered sustainable energy sources.

Water Technology and Desalination

Less than 1% of the earth’s water is freshwater, and even this amount is unevenly distributed across the planet.
one in ten people globally lack ready access to clean water
Urbanization also plays a big role in water scarcity with many large cities facing water stress.

Agtech Companies and Stocks

Most of us rely on a small percentage of the population who grow food for all the rest of us.
Since land is scarce, we’re having to come up with more creative ways to increase yields on the same footprint.

Agtech in New Zealand
- gross stuff on herd management completely missing the point of where things are going
Indoor Farming
- Attractive business models will provide vegetables at scale with price points at or under regular vegetable prices.
- From what we’ve seen so far, container farming is not economically viable.
Agtech Stocks
- We have only come across a few names that would be considered pure-plays on the agtech theme.

Food Technology Companies and Stocks

Food technology is when we start to play with producing food in ways we hadn’t thought of
most of the buzz in food tech is mainly around the whole fake meat boom

Lab-Grown Meat
- fake food which simply refers to the many types of foods that are now being produced which are supposed to resemble the organically produced thing

Investing in Electric Vehicles and EV Charging

Improved battery efficiencies, faster charging times, and an ever-expanding network of charging stations make electric cars appealing to a broader set of potential buyers. guide

Investing in Batteries and Grid Storage

The Growth of Lithium-Ion Batteries
- As battery technology improves, expect more things to be electrified.
- Another type of battery being developed by a number of companies is the solid-state battery which uses both solid electrodes and solid electrolytes, instead of the liquid or polymer electrolytes found in lithium-ion or lithium polymer batteries.
- Investors remain interested in lithium as an investment thesis
Grid Storage
- Grid-scale energy storage is about using batteries to store energy instead. We can’t just go around building reservoirs when we need them.
- A flow battery is a type of rechargeable battery in which large tanks of chemicals are used to create chemical energy which is then converted to electricity.
- the humble lead-acid battery that’s found in most motor vehicles is also being looked at for a renovation

Waste Management Stocks and Companies

It’s not just about recycling more plastic, it’s about improving the recycling process itself.
Industrial waste management is not just about plastics. Municipal solid waste (MSW) needs to get sorted first so that garbage plants can get to the recyclable part.

Investing in LED Technologies

LEDs can last up to 25 times longer than an ordinary incandescent bulb, and use 75% percent less energy to produce the same amount of light.
There’s still plenty of innovation still to be found from exciting startups

Penny Stocks, Stock Promoters, and Shills

When you see a stock soaring for no reason, go to the investment message boards like InvestorsHub and see if it’s being pumped by shills.
Whatever you do, don’t invest in any stock that doesn’t trade on a major exchange. That’s rule one.

Does Sustainable Investing Outperform?

Green-tech investing goes by a number of names such as sustainable investing, socially responsible investing (SRI), impact investing, environmental, social and governance (ESG) investing
Just make sure that your money is being put into companies that everyone agrees are sustainable, and make sure you understand what they consider sustainable to be.

Internet of Things

IoT which describes a world where everything is connected. That connectivity isn’t just everything talking to the cloud, it’s about machines talking to machines or (M2M).
We’d like to start with talking about industrial applications for IoT and the concept of a “digital twin.”

IoT Sensors and Digital Twins

a digital twin is when you create a digital representation of something like a machine on a factory floor or even the entire factory

The Emergence of Smart Cities

The smart city of tomorrow is one where IoT sensors and big data enable us to create better places for people to live

Smart Homes

A smart home is one that minimizes energy use and utility costs while providing a safe and secure location with all the conveniences you’d expect.

IoT Across Multiple Industries

new IoT-enabled medical devices that collect loads of data for AI algorithms to analyze
multiple startups pursue “Uber for trucking” business models
In the automotive industry, connected cars now talk to the cloud, and even each other
Using IoT sensor technology, we’re able to increase yields in agriculture and aquaculture.
IoT use cases abound in areas such as shoplifting prevention or “free wifi hotspot marketing.”

Investing in IoT Stocks

Given how thought leaders are predicting that IoT will transform nearly everything around us, you’re probably wanting to “invest in some IoT stocks.”
There is at least one ETF covering the IoT theme – The Global X Internet of Things ETF (SNSR)
investing in smart homes, you might consider Alarm.com (ALRM)
A few members of the ETF have exposure to IoT along with a number of other disruptive technologies.

IoT – The Threats

IoT is still having some growing pains as we wait for 5G to give us more bandwidth.
some understandable privacy concerns around IoT technology that haven’t gone unnoticed

Life Sciences

especially since this effort would end research using animals
a broad topic that encompasses around 30 different branches of study
Oftentimes we’ll find groups of startups trying to solve similar problems
Many of the problems being worked on involve cures that haven’t been developed yet, something we looked at in our “when will there be a cure” series.
we’ve tried to narrow it all down to six areas of focus

Genomics

Using genetic sequencing machines, scientists are not only able to read the recipes of life, they’re also able to edit them
Huge databases of DNA data are now being mined for insights, and scientists are even able to reconstruct composite images of criminals from crime scenes using DNA, something referred to as DNA phenotyping.
In the future, we’ll have a world where everyone is given personalized medicine tailored to their unique genetic makeup.

Investing in Genomics Stocks
- Illumina, a company that all but dominates the market for machines that perform gene sequencing
- Not all genomics stocks are leaders. There are plenty of laggards
- ARK Invest likes BNGO and that’s sent the stock soaring to the moon

Human Longevity

extending the human lifespan by rolling back the effects of aging
Venture capitalists are pouring money into dozens of startups tackling the aging problem in areas like regenerative medicine or young blood transfusions.

Medical Devices and Imaging

in the medical industry where connected medical devices allow doctors to monitor patients’ vital signs from afar

Medical Imaging
- some of the biggest advancements are being made in medical imaging where deep learning algorithms are used to interpret medical imagery
Telehealth
- The increasing sophistication of medical devices and medical imaging algorithms mean that doctors are more easily able to treat patients from afar.
Big Data in Healthcare
- Many data analytics businesses are emerging which use this data for predictive analytics or to identify inefficiencies in processes.

Brain-Computer Interfaces

A brain-computer interface might be the Holy Grail for human advancement.

The Drug Discovery Process

Plenty of companies are working on removing all the inefficiencies from the process.

Medical Testing

advancements in medical testing could prove to save lives and money

Cancer Genomics Testing
- It isn’t just about early detection, it’s also about finding the most effective cancer treatment and monitoring its progress.
- There are also companies developing cancer therapies that are fine-tuned to certain genomic profiles like personalized chemotherapy.
Genetics Testing
- There are now genetic tests for nearly everything, including genetics tests for pets.
- The evolution of genetics testing is now leading to new business models that try to adapt to the environment.

Other Life Sciences Themes

The Diabetes Opportunity
- fat asses abound because people drive up to windows to consume two days of calories in one seating – which they then wash down with a diet soda.
- The hard truth is that obesity is unhealthy and a contributing factor to a huge global problem – diabetes.
Non-Invasive Prenatal Testing (NIPT)
- It’s a test that makes sure your little bundle of joy doesn’t pop out with two heads, or be afflicted by any malady that would interfere with the perfect life you’ve planned for it.
Stem Cells
- These are useful for applications like regenerating body parts or figuring out what makes cancer cells replicate.

Things We Don’t Understand Very Well

It’s very difficult to understand some of these businesses without having a medical background, and if you need eight years of training to understand what a company does, it’s probably too complex for retail investors.

RNAi Therapeutics
- Instead of spending hours trying to understand how microRNA relates to RNAi, we’re staying away from drug development companies entirely.

Interesting Life Sciences Stocks

Given the breadth of technologies to be found under life sciences, we often take fleeting looks at companies that are doing cool things without necessarily doing any deep-dives or follow-ups.

Penny Stocks and OTC Stocks

Investing in any of these companies would have proved to be a total disaster. Of course, there are always some exceptions, but why try to walk through landmines to find them?

Conclusion

Because life sciences is such a broad category, you’ll find it peppered throughout all the twelve categories of disruptive technologies

Nanotechnology

What is Nanotechnology?

the study of anything that measures less than 100 nanometers

How Nanotechnology Has Evolved

Nanotechnology Penny Stocks
- In reading about companies that have failed, we can better understand how to find those that will succeed.
- We also found that the same companies that were promising us nanomaterial breakthroughs in 2004 were still making those same promises nine years later.
What Happened to Nanomaterials?
- we just can’t take companies seriously that continue to promise revenues and never deliver on them
- People quickly forgot about how the carbon nanotube was expected to change the world when it was replaced by another promising nanostructure called graphene.
- Graphene is a sheet of atoms that you can pick up.
- Researchers keep talking about all the great things they can do with quantum dots but commercialized applications seem far and few between.
- There is no shortage of interesting nanomaterials out there
- There are also applications for nano that can help heal the planet.
- There are a lot of exciting things happening in the world of nanotechnology, so let’s see how retail investors might be able to get some exposure to nano stocks.

Investing in Nanotechnology Stocks

Nanotechnology ETFs
- there are no nanotechnology ETFs right now
Nanotechnology Companies That Stagnated
- We’ve talked about how prolific nano penny stocks were, but we haven’t talked about more legitimate companies with revenues that haven’t been able to quite take off yet.
- break down the nanotechnology opportunity into three major themes: nanomaterials including graphene, nano-drug delivery, and synthetic biology including gene editing
Investing in Nanomaterials and Graphene
- What investors need to remember is that companies which use nanomaterials for a competitive advantage won’t necessarily be telling the world about it.
Investing in Synthetic Biology and Gene Editing
- the single most exciting disruptive technology there is, that would have to be synthetic biology
- Many futurist-minded people are thinking that soon we’ll just grow everything we need using tools like gene editing.

Investing in Nanomedicine

applications for nanotechnology in the healthcare sector are many

Investing in Nano Drug Delivery
- many drug companies actively use nanoparticles to deliver drugs more efficiently

Space

Will NewSpace, the term that describes the new era of commercial-driven space exploration, supernova into a trillion-dollar business?
Risk-averse investors will want to hold onto their money when it comes to the high-risk business of operating in space.

Investing in Global Internet

SpaceX appears poised to run away with the global internet race, as it sends thousands of satellites into low Earth orbit (LEO), as part of the Starlink constellation to provide billions of people with connectivity and cute cat videos
the smart money is that the impact of cheap satellites and launch platforms will give massive undertakings like the SpaceX Starlink constellation the edge

Investing in Satellite Companies

still pretty hard to get exposure to the “space theme” without ending up with a portfolio filled with either big tech stocks like Amazon or Google or a bunch of companies that make rockets aimed in the wrong direction
As much as 75% of the NewSpace industry is dominated by the satellite sector, which includes everything from manufacturing spacecraft to providing communications services.

Investing in Geospatial Intelligence from Satellites

sector of the satellite industry where we’re seeing both tremendous growth and potential is in geospatial intelligence
there are a few geospatial intelligence stocks out there
One of the biggest risks to the satellite industry is the satellite industry … New technologies for space debris removal will become extremely important

Rocket Companies Launch a New Space Race

we would expect a high rate of failure in this sector, as there’s still not enough business to justify the numerous rocket startups that have emerged
China is becoming a serious contender in space with new startups building rockets and satellites

Mining the Moon for Money

The moon is home to various precious metals and rare minerals that are integral to our technologies.

Investing in Space Tourism

Since then, there have been very few opportunities for the common man or woman to enjoy a romp in zero gravity
ISS has been floated as a possible tourist destination once the scientific mission there ends
there’s not much gold to mine in space just yet

Robotics

The first time the word “robot” was used was when Karel Capek introduced it in his 1920 hit play RUR

Why Is Robotics Important?

Robotics is becoming increasingly important because the companies using them are gaining a competitive advantage.

Where is Robotic Technology Today?

Robotics applications are growing in popularity because of technologies like machine learning that help the robots work more like humans, perhaps handling unexpected exceptions without just ceasing to operate.

Drone Stocks and Companies

Drones are usually categorized into military, commercial, and consumer segments which neatly cover most of the current use cases.

Drone Delivery
- The jury is still out on what type of drone delivery model will be adopted at scale, if any. For retail investors, we haven’t seen any pure-play opportunities to invest in drone delivery.
Industrial Drones
- industrial drones are another use case under the “commercial” category
  - industrial inspection
  - aerial information
  - reconnaissance, search and rescue
  - warehouse management
Military and Security Drones
- The military use of drones is growing at an unprecedented rate in the U.S.
- The other opportunity is security drones for civilian use cases such as replacing rent-a-cops.
- round-the-clock surveillance means that battery swapping needs to take place
Consumer Drones and Other Types of Drones
- Crowdfunding seems to be the funding method of choice for manufacturers of small, low-cost UAVs.
Where Are the Drone Stocks?
- Pure-play drone stocks are hard to come by.
- Plenty of drone startups failed too.
- The drone market remains in private hands for now

Investing in Autonomous Vehicles

Levels of Autonomy
- Autonomous vehicles (or driverless cars) are an overlap of a number of disruptive technologies.
- 5 levels
What do Autonomous Vehicles Need to Work?
- autonomous cars need uniquely tailored perception systems LiDAR
- High-definition maps, that are precise to a centimeter, are required to navigate any environment safely.
- vehicle’s artificial intelligence algorithms need to react correctly to any situation
Autonomous Trucking
- the industry created its own little startup ecosystem with companies developing applications for fuel efficiency, fleet management, and kits that can upgrade any truck to a self-driving vehicle
Autonomous Vehicles That Aren’t Cars
- Autonomous boats promise to navigate more economically and efficiently than humans do now.
- large corporations like IBM are working on autonomous shipping
- autonomous heavy construction equipment with conversion kits for excavators, bulldozers, and skid steers
- Autonomous planes are also in the making
- Autonomous robots, tractors, trains, and of course, the Hyperloop are the icing on the cake of autonomous technologies.

Investing in Industrial Robotics

industrial robotics is currently the largest application area for robots by far
industrial robot prices are declining and will continue to do so, which will result in industrial robot sales quadrupling during the next five years as more companies move to adopt them

Robots for Factory Automation
- While there are many startups working on robotics for factory automation, there also happen to be many listed companies doing the same which is great for retail investors who want exposure to this theme.
- China is becoming a large consumer of robotics
Robots for Warehouse Automation
- Warehouse robots range from plug-and-play systems and forklifts working alongside humans to infrastructure systems that can fully automate warehouses – what they’re calling “lights out operations.”
- Today’s warehouse robots are capable of full autonomy either alone or side-by-side with humans, thanks to AI algorithms.
Companies Developing Machine Vision and Industrial Cameras
- The eyes are provided by machine vision systems, the mouth by natural language processing, and the body by robotics.
Robots Replacing Humans Doing the Worst Jobs
- Industrial inspection tasks, maintenance, and high-rise window cleaning are all examples of relatively dangerous and time-consuming jobs.

Robots in Healthcare

Robots are helping in elderly care and the daily operations of smart hospitals. Robotics technology is being used to create bionic limbs and help dental surgeons perform implants.
the area where healthcare robots really shine is robotic surgery

Robotic Surgery Stocks and Companies
- at least eight different types of surgeries that are now being performed or partially performed by robots

Robots for Consumers

first large-scale implementation of consumer robotics was iRobot’s robotic vacuums
all these types of robots will be made in China

Robotics ETFs

The problem is that most of these robotics ETFs can’t agree on which companies to include.
it makes us wonder how the ESG types plan to address robotics as an investment thesis

Other resources

Singularity University

Exponential Business Models | Amin Toufani: Exponential times require exponential business models.

Exonomics | Amin Toufani: transform industries and global challenges through exponential technologies

Exponential Energy | Ramez Naam: overview of the key natural resource and environmental challenges

Investing in disruptive innovation | Cathie Woods: Investing in disruptive innovation

Useful sites

amin toufani ramez naam

Videos

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