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A Model in Place of an Animal: Who Accepts In-Silico Evidence, by When, and What Reopens It · The study

Sources and bibliography

By RISCON Labs AI from public-domain and openly licensed sources on in-silico drug discovery · not medical advice · the readings through the works named are this study's interpretation · First edition · October 2026

AI-generated editorial illustration: A model vessel faces a laboratory testing chamber across an unconnected gap.
A Model in Place of an Animal: Who Accepts In-Silico Evidence, by When, and What Reopens ItOpening
In this part
In this part
  1. Bibliography

This study is an expansion by AI of eleven public texts on in-silico drug discovery and its regulation. Seven are works of the United States government, in the public domain: two sections of the 21st Century Cures Act, two sections of the Consolidated Appropriations Act, 2023 (the FDA Modernization Act 2.0), the FDA Modernization Act 3.0 as introduced in the Senate, a Federal Register notice of a draft guidance, the draft guidance's landing page, an FDA press announcement and an FDA topic page. Four are articles published under the Creative Commons Attribution 4.0 licence, read in full from PubMed Central. Every passage in a block quote is one of these texts, word for word, and its source line names the saved file; the rest is AI writing. Nothing here is medical, clinical, regulatory or investment advice. The readings through the works named are this study's interpretation.

TextLicenceAddress
Considerations for the Use of Artificial Intelligence To Support Regulatory Decision-Making for Drug and Biological Products; Draft Guidance for Industry; Availability; Comment Request (2025), sources/fda-ai-draft-guidance-federal-register-notice-2025.mdPublic domain (US government work)https://www.govinfo.gov/content/pkg/FR-2025-01-07/html/2024-31542.htm
FDA Modernization Act 3.0 (S. 355, 119th Congress, as introduced) (2025), sources/fda-modernization-act-3-0-s355-119th-congress.mdPublic domain (US government work)https://www.govinfo.gov/content/pkg/BILLS-119s355is/html/BILLS-119s355is.htm
Consolidated Appropriations Act, 2023 (Public Law 117-328), Sec. 3209 'Animal Testing Alternatives' (FDA Modernization Act 2.0) and Sec. 3507 (excerpt) (2022), sources/fda-modernization-act-2-0-pl117-328-sec3209-3507.mdPublic domain (US government work)https://www.govinfo.gov/content/pkg/PLAW-117publ328/html/PLAW-117publ328.htm
21st Century Cures Act (Public Law 114-255), Sec. 3011 'Qualification of Drug Development Tools' and Sec. 3022 'Real World Evidence' (excerpt) (2016), sources/21st-century-cures-act-pl114-255-sec3011-3022.mdPublic domain (US government work)https://www.govinfo.gov/content/pkg/PLAW-114publ255/html/PLAW-114publ255.htm
FDA Modernization Act 2.0: transitioning beyond animal models with human cells, organoids, and AI/ML-based approaches (2023), sources/zushin-2023-fda-modernization-act-2.mdCC BY 4.0https://pmc.ncbi.nlm.nih.gov/articles/PMC10617761/
Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 2: a discussion of chemical and biological data (2021), sources/bender-2021-artificial-intelligence-drug-discovery.mdCC BY 4.0https://pmc.ncbi.nlm.nih.gov/articles/PMC8132984/
In silico trials: Verification, validation and uncertainty quantification of predictive models used in the regulatory evaluation of biomedical products (2021), sources/viceconti-2021-silico-trials-verification-validation.mdCC BY 4.0https://pmc.ncbi.nlm.nih.gov/articles/PMC7883933/
AI in drug discovery and its clinical relevance (2023), sources/qureshi-2023-ai-drug-discovery-its.mdCC BY 4.0https://pmc.ncbi.nlm.nih.gov/articles/PMC10302550/
Considerations for the Use of Artificial Intelligence to Support Regulatory Decision-Making for Drug and Biological Products (draft guidance, FDA landing page) (2025), sources/fda-ai-draft-guidance-landing-page-2025.mdPublic domain (US government work)https://www.fda.gov/regulatory-information/search-fda-guidance-documents/considerations-use-artificial-intelligence-support-regulatory-decision-making-drug-and-biological
Artificial Intelligence for Drug Development (FDA topic page; links the 2023 discussion paper) (2025), sources/fda-artificial-intelligence-drug-development-page.mdPublic domain (US government work)https://www.fda.gov/science-research/science-and-research-special-topics/artificial-intelligence-and-machine-learning-aiml-drug-development
FDA Announces Plan to Phase Out Animal Testing Requirement for Monoclonal Antibodies and Other Drugs (2025), sources/fda-2025-plan-phase-out-animal-testing.mdPublic domain (US government work)https://www.fda.gov/news-events/press-announcements/fda-announces-plan-phase-out-animal-testing-requirement-monoclonal-antibodies-and-other-drugs

The texts were retrieved on 2026-10-06. The European Medicines Agency reflection paper listed in the manifest was held only as a bibliographic record and is not quoted. This book was written on 2026-10-07.

Bibliography

  • Marco Viceconti and others, In silico trials: Verification, validation and uncertainty quantification of predictive models used in the regulatory evaluation of biomedical products (2021).
  • Andreas Bender and Isidro Cortes-Ciriano, Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 2: a discussion of chemical and biological data (2021).
  • Rizwan Qureshi and others, AI in drug discovery and its clinical relevance (2023).
  • Peter-James H. Zushin and others, FDA Modernization Act 2.0: transitioning beyond animal models with human cells, organoids, and AI/ML-based approaches (2023).
  • Rajanikanth Madabushi and others, Review: Role of Model-Informed Drug Development Approaches in the Lifecycle of Drug Development and Regulatory Decision-Making (2022).
  • Jack W. Scannell and others, Diagnosing the decline in pharmaceutical R&D efficiency (2012).
  • Petra Schneider and others, Rethinking drug design in the artificial intelligence era (2019).
  • Jessica Vamathevan and others, Applications of machine learning in drug discovery and development (2019).
  • U.S. Congress, 21st Century Cures Act (2016): Public Law 114-255, sections 3011 and 3022.
  • U.S. Congress, Consolidated Appropriations Act, 2023 (2022): Public Law 117-328, sections 3209 (the FDA Modernization Act 2.0) and 3507.
  • U.S. Food and Drug Administration, Considerations for the Use of Artificial Intelligence to Support Regulatory Decision-Making for Drug and Biological Products (2025): draft guidance, docket FDA-2024-D-4689.
  • U.S. Food and Drug Administration, FDA Announces Plan to Phase Out Animal Testing Requirement for Monoclonal Antibodies and Other Drugs (2025): press announcement.
  • U.S. Food and Drug Administration, Artificial Intelligence for Drug Development (2025): topic page of the Center for Drug Evaluation and Research.

Every sentence in a quotation block is IATHEON's record, word for word. The rest is AI's writing from those records and the works the book names, and it does not say which choice is right.

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