Abstract
The development of new approach methodologies (NAMs) and advances with in vitro testing systems have prompted revisions in regulatory guidelines and inspired dedicated in vitro/ex vivo studies for nonclinical safety assessment. This Review by a safety reflection initiative subgroup of the European Federation of Pharmaceutical Industries and Associations (EFPIA)/Preclinical Development Expert Group (PDEG) summarizes the current state and potential application of in vitro studies using human-derived material for safety assessment in drug development. It focuses on case studies from recent projects in which animal models alone proved to be limited or inadequate for safety testing. It further highlights four categories of drug candidates for which alternative in vitro approaches are applicable and discusses progress in using in vitro testing solutions for safety assessment in these categories. Finally, the article highlights new risk assessment strategies, initiatives and consortia promoting the advancement of NAMs. This collective work is meant to encourage the use of NAMs for more human-relevant safety assessment, which should ultimately result in reduced animal testing for drug development.
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References
Greaves, P., Williams, A. & Eve, M. First dose of potential new medicines to humans: how animals help. Nat. Rev. Drug Discov. 3, 226–236 (2004).
Monticello, T. M. et al. Current nonclinical testing paradigm enables safe entry to first-in-human clinical trials: the IQ consortium nonclinical to clinical translational database. Toxicol. Appl. Pharm. 334, 100–109 (2017).
Bailey, J., Thew, M. & Balls, M. An analysis of the use of animal models in predicting human toxicology and drug safety. Altern. Lab. Anim. 42, 181–199 (2014).
Waring, M. J. et al. An analysis of the attrition of drug candidates from four major pharmaceutical companies. Nat. Rev. Drug Discov. 14, 475–486 (2015).
Martignoni, M., Groothuis, G. M. M. & de Kanter, R. Species differences between mouse, rat, dog, monkey and human CYP-mediated drug metabolism, inhibition and induction. Expert Opin. Drug Met. 2, 875–894 (2006).
Kararli, T. T. Comparison of the gastrointestinal anatomy, physiology, and biochemistry of humans and commonly used laboratory animals. Biopharm. Drug Dispos. 16, 351–380 (1995).
Bjornson-Hooper, Z. B. et al. A comprehensive atlas of immunological differences between humans, mice and non-human primates. Front. Immunol. 13, 867015 (2022).
Krause, C. et al. Preclinical species gene expression database: development and meta-analysis. Front. Genet. 13, 1078050 (2023).
Worley, K. C. et al. The common marmoset genome provides insight into primate biology and evolution. Nat. Genet. 46, 850–857 (2014).
Namdari, R. et al. Species selection for nonclinical safety assessment of drug candidates: examples of current industry practice. Regul. Toxicol. Pharm. 126, 105029 (2021).
European Medicines Agency. Guideline on strategies to identify and mitigate risks for first-in-human and early clinical trials with investigational medicinal products. https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-strategies-identify-mitigate-risks-first-human-early-clinical-trials-investigational_en.pdf (2017).
Food and Drug Administration, HHS. International Conference on Harmonisation; addendum to International Conference on Harmonisation Guidance on S6 Preclinical Safety Evaluation of Biotechnology-Derived Pharmaceuticals; availability. Notice. Fed. Regist. 77, 29665–29666 (2012).
Congress, 117th US. S.5002—FDA Modernization Act 2.0 117th Congress (2021-2022). https://www.congress.gov/bill/117th-congress/senate-bill/5002 (2022).
Avila, A. M. et al. An FDA/CDER perspective on nonclinical testing strategies: classical toxicology approaches and new approach methodologies (NAMs). Regul. Toxicol. Pharmacol. 114, 104662 (2020).
Avila, A. M. et al. Gaps and challenges in nonclinical assessments of pharmaceuticals: an FDA/CDER perspective on considerations for development of new approach methodologies. Regul. Toxicol. Pharmacol. 139, 105345 (2023).
Kitano, H. Biological robustness. Nat. Rev. Genet. 5, 826–837 (2004).
Clark, M. & Steger-Hartmann, T. A big data approach to the concordance of the toxicity of pharmaceuticals in animals and humans. Regul. Toxicol. Pharm. 96, 94–105 (2018).
NRamos, K. S., Downey, A. & Yost, O. C. (eds). Nonhuman Primate Models in Biomedical Research. https://doi.org/10.17226/26857 (2023).
Pognan, F. et al. The evolving role of investigative toxicology in the pharmaceutical industry. Nat. Rev. Drug Discov. 22, 317–335 (2023).
Schaller, T. H. et al. First in human dose calculation of a single-chain bispecific antibody targeting glioma using the MABEL approach. J. Immunother. Cancer 8, e000213 (2020).
Ji, Y. et al. Model‐informed drug development for immuno‐oncology agonistic anti‐GITR antibody GWN323: dose selection based on MABEL and biologically active dose. Clin. Transl. Sci. 15, 2218–2229 (2022).
Dudal, S. et al. Application of a MABEL approach for a T-cell-bispecific monoclonal antibody. J. Immunother. 39, 279–289 (2016).
Muller, P. Y., Milton, M., Lloyd, P., Sims, J. & Brennan, F. R. The minimum anticipated biological effect level (MABEL) for selection of first human dose in clinical trials with monoclonal antibodies. Curr. Opin. Biotechnol. 20, 722–729 (2009).
Beilmann, M. et al. Optimizing drug discovery by investigative toxicology: current and future trends. ALTEX 36, 289–313 (2018).
Mulder, P. et al. Predicting cardiac safety using human induced pluripotent stem cell-derived cardiomyocytes combined with multi-electrode array (MEA) technology: a conference report. J. Pharmacol. Toxicol. Methods 91, 36–42 (2018).
Rana, P., Aleo, M. D., Gosink, M. & Will, Y. Evaluation of in vitro mitochondrial toxicity assays and physicochemical properties for prediction of organ toxicity using 228 pharmaceutical drugs. Chem. Res. Toxicol. 32, 156–167 (2019).
Hynes, J., Carey, C. & Will, Y. Fluorescence‐based microplate assays for in vitro assessment of mitochondrial toxicity, metabolic perturbation, and cellular oxygenation. Curr. Protoc. Toxicol. 70, 2.16.1–2.16.30 (2016).
Matsui, T. & Shinozawa, T. Human organoids for predictive toxicology research and drug development. Front. Genet. 12, 767621 (2021).
Mina, S. G. et al. Assessment of drug-induced toxicity biomarkers in the brain microphysiological system (MPS) using targeted and untargeted molecular profiling. Front. Big Data 2, 23 (2019).
Wang, X. et al. Application of immunocompetent microphysiological systems in drug development: current perspective and recommendations. ALTEX 40, 314–336 (2022).
Gjorevski, N. et al. Neutrophilic infiltration in organ-on-a-chip model of tissue inflammation. Lab. Chip 20, 3365–3374 (2020).
McAleer, C. W. et al. Multi-organ system for the evaluation of efficacy and off-target toxicity of anticancer therapeutics. Sci. Transl. Med. 11, eaav1386 (2019).
Carmichael, P. L. et al. Ready for regulatory use: NAMs and NGRA for chemical safety assurance. Altex 39, 359–366 (2022).
Mozneb, M. et al. Multi-lineage heart-chip models drug cardiotoxicity and enhances maturation of human stem cell-derived cardiovascular cells. Lab. Chip 24, 869–881 (2024).
Liu, S., Fang, C., Zhong, C., Li, J. & Xiao, Q. Recent advances in pluripotent stem cell-derived cardiac organoids and heart-on-chip applications for studying anti-cancer drug-induced cardiotoxicity. Cell Biol. Toxicol. 39, 2527–2549 (2023).
Roux, G. L. et al. Proof-of-concept study of drug brain permeability between in vivo human brain and an in vitro iPSCs-human blood-brain barrier model. Sci. Rep. 9, 16310 (2019).
Hajal, C. et al. Engineered human blood–brain barrier microfluidic model for vascular permeability analyses. Nat. Protoc. 17, 95–128 (2022).
Harper, J. et al. An approved in vitro approach to preclinical safety and efficacy evaluation of engineered T cell receptor anti-CD3 bispecific (ImmTAC) molecules. PLoS ONE 13, e0205491 (2018).
Parng, C. et al. Induction and impact of anti-drug responses elicited by a human recombinant coagulation factor FXaI16L in preclinical species. AAPS J. 21, 52 (2019).
Clarke, J. et al. Evaluation of a surrogate antibody for preclinical safety testing of an anti-CD11a monoclonal antibody. Regul. Toxicol. Pharmacol. 40, 219–226 (2004).
Bugelski, P. J. & Martin, P. L. Concordance of preclinical and clinical pharmacology and toxicology of therapeutic monoclonal antibodies and fusion proteins: cell surface targets. Br. J. Pharmacol. 166, 823–846 (2012).
Martin, P. L. & Bugelski, P. J. Concordance of preclinical and clinical pharmacology and toxicology of monoclonal antibodies and fusion proteins: soluble targets. Br. J. Pharmacol. 166, 806–822 (2012).
Boudousquie, C. et al. Polyfunctional response by ImmTAC (IMCgp100) redirected CD8+ and CD4+ T cells. Immunology 152, 425–438 (2017).
Howlett, S., Carter, T. J., Shaw, H. M. & Nathan, P. D. Tebentafusp: a first-in-class treatment for metastatic uveal melanoma. Ther. Adv. Méd. Oncol. 15, 17588359231160140 (2023).
Ryan, P. C. et al. In vitro MABEL approach for nonclinical safety assessment of MEDI-565 (MT111). ALTEX Proceedings, 1/12, Proceedings of W8. https://proceedings.altex.org/data/2012-01/085087_Ryan31.pdf (2012).
Moek, K. L. et al. 427P. Phase I study of AMG 211/MEDI-565 administered as continuous intravenous infusion (cIV) for relapsed/refractory gastrointestinal (GI) adenocarcinoma. Ann. Oncol. 29, viii139–viii140 (2018).
Pishvaian, M. et al. Phase 1 dose escalation study of MEDI-565, a bispecific T-cell engager that targets human carcinoembryonic antigen, in patients with advanced gastrointestinal adenocarcinomas. Clin. Colorectal Cancer 15, 345–351 (2016).
Kinugasa, T. et al. Expression of four CEA family antigens (CEA, NCA, BGP and CGM2) in normal and cancerous gastric epithelial cells: up‐regulation of BGP and CGM2 in carcinomas. Int. J. Cancer 76, 148–153 (1998).
Teijeira, A. et al. Three-dimensional colon cancer organoids model the response to CEA-CD3 T-cell engagers. Theranostics 12, 1373–1387 (2022).
Harter, M. F. et al. Analysis of off-tumour toxicities of T-cell-engaging bispecific antibodies via donor-matched intestinal organoids and tumouroids. Nat. Biomed. Eng. 8, 345–360 (2024).
Kebenko, M. et al. A multicenter phase 1 study of solitomab (MT110, AMG 110), a bispecific EpCAM/CD3 T-cell engager (BiTE®) antibody construct, in patients with refractory solid tumors. Oncoimmunology 7, e1450710 (2018).
Wang, L. et al. Efficient tumor regression by adoptively transferred CEA-specific CAR-T cells associated with symptoms of mild cytokine release syndrome. Oncoimmunology 5, e1211218 (2016).
Amann, M. et al. Therapeutic window of MuS110, a single-chain antibody construct bispecific for murine EpCAM and murine CD3. Cancer Res. 68, 143–151 (2008).
Park, S. E., Georgescu, A. & Huh, D. Organoids-on-a-chip. Science 364, 960–965 (2019).
Bar-Ephraim, Y. E., Kretzschmar, K. & Clevers, H. Organoids in immunological research. Nat. Rev. Immunol. 20, 279–293 (2020).
Hammel, J. H., Cook, S. R., Belanger, M. C., Munson, J. M. & Pompano, R. R. Modeling immunity in vitro: slices, chips, and engineered tissues. Annu. Rev. Biomed. Eng. 23, 461–491 (2021).
Ronaldson-Bouchard, K. et al. A multi-organ chip with matured tissue niches linked by vascular flow. Nat. Biomed. Eng. 6, 351–371 (2022).
Koning, J. J. et al. A multi-organ-on-chip approach to investigate how oral exposure to metals can cause systemic toxicity leading to Langerhans cell activation in skin. Front. Toxicol. 3, 824825 (2022).
Tao, T. et al. Microengineered multi‐organoid system from hiPSCs to recapitulate human liver‐islet axis in normal and type 2 diabetes. Adv. Sci. 9, 2103495 (2022).
Cecen, B. et al. Multi-organs-on-chips for testing small-molecule drugs: challenges and perspectives. Pharmaceutics 13, 1657 (2021).
Mandrycky, C. J., Howard, C. C., Rayner, S. G., Shin, Y. J. & Zheng, Y. Organ-on-a-chip systems for vascular biology. J. Mol. Cell Cardiol. 159, 1–13 (2021).
Hachey, S. J. et al. A human vascularized micro-tumor model of patient-derived colorectal cancer recapitulates clinical disease. Transl. Res. 255, 97–108 (2022).
Kim, S., Wan, Z., Jeon, J. S. & Kamm, R. D. Microfluidic vascular models of tumor cell extravasation. Front. Oncol. 12, 1052192 (2022).
Palikuqi, B. et al. Adaptable haemodynamic endothelial cells for organogenesis and tumorigenesis. Nature 585, 426–432 (2020).
Yu, J. et al. Perfusable micro-vascularized 3D tissue array for high-throughput vascular phenotypic screening. Nano Converg. 9, 16 (2022).
Johnson, D. E. & Wolfgang, G. H. I. Predicting human safety: screening and computational approaches. Drug Discov. Today 5, 445–454 (2000).
Mestres, J. & Gregori-Puigjané, E. Conciliating binding efficiency and polypharmacology. Trends Pharmacol. Sci. 30, 470–474 (2009).
Peón, A., Naulaerts, S. & Ballester, P. J. Predicting the reliability of drug-target interaction predictions with maximum coverage of target space. Sci. Rep. 7, 3820 (2017).
Metz, J. T. & Hajduk, P. J. Rational approaches to targeted polypharmacology: creating and navigating protein–ligand interaction networks. Curr. Opin. Chem. Biol. 14, 498–504 (2010).
Gradl, S. et al. Abstract ND04: BAY 2666605: the first PDE3A-SLFN12 complex inducer for cancer therapy. Cancer Res. 82(12 Suppl.), ND04 (2022).
Garvie, C. W. et al. Structure of PDE3A-SLFN12 complex reveals requirements for activation of SLFN12 RNase. Nat. Commun. 12, 4375 (2021).
Greulich, H. Velcrin compounds activate the SLFN12 tRNase to induce tomoptosis. Cell Chem. Biol. 31, 1039–1043 (2024).
Lewis, T. A. et al. Discovery of BAY 2666605, a molecular glue for PDE3A and SLFN12. ACS Med. Chem. Lett. 15, 1662–1667 (2024).
Zhu, K. et al. HER2-targeted therapies in cancer: a systematic review. Biomark. Res. 12, 16 (2024).
Phillips, G. L. et al. Trastuzumab does not bind rat or mouse ErbB2/neu: implications for selection of non-clinical safety models for trastuzumab-based therapeutics. Breast Cancer Res. Treat. 191, 303–317 (2022).
Dokter, W. et al. Preclinical profile of the HER2-targeting ADC SYD983/SYD985: introduction of a new duocarmycin-based linker-drug platform. Mol. Cancer Ther. 13, 2618–2629 (2014).
Hosseini, V. et al. Healthy and diseased in vitro models of vascular systems. Lab. Chip 21, 641–659 (2021).
Cochrane, A. et al. Advanced in vitro models of vascular biology: human induced pluripotent stem cells and organ-on-chip technology. Adv. Drug Deliv. Rev. 140, 68–77 (2019).
Ceyzériat, K. et al. Learning from the past: a review of clinical trials targeting amyloid, Tau and neuroinflammation in Alzheimer’s disease. Curr. Alzheimer Res. 17, 112–125 (2020).
World Health Organization. World -malaria report 2021. https://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2021 (2021).
Barber, J. et al. A target safety assessment of the potential toxicological risks of targeting plasmepsin IX/X for the treatment of malaria. Toxicol. Res. 10, 203–213 (2021).
Barber, N. M. et al. Structure-guided design of a synthetic mimic of an endothelial protein C receptor-binding PfEMP1 protein. mSphere 6, e01081-20 (2021).
Hewitt, P. et al. An innovative study design with intermittent dosing to generate a GLP-regulatory package in preclinical species for long lasting molecule M5717, inhibitor of Plasmodium eukaryotic translation elongation factor 2. Toxicol. Appl. Pharm. 443, 116006 (2022).
Baragaña, B. et al. A novel multiple-stage antimalarial agent that inhibits protein synthesis. Nature 522, 315–320 (2015).
McCarthy, J. S. et al. Safety, pharmacokinetics, and antimalarial activity of the novel plasmodium eukaryotic translation elongation factor 2 inhibitor M5717: a first-in-human, randomised, placebo-controlled, double-blind, single ascending dose study and volunteer infection study. Lancet Infect. Dis. 21, 1713–1724 (2021).
Feng, J. Y. Addressing the selectivity and toxicity of antiviral nucleosides. Antivir. Chem. Chemother. 26, 2040206618758524 (2018).
Kiy, R. T., Khoo, S. H. & Chadwick, A. E. Assessing the mitochondrial safety profile of the molnupiravir active metabolite, β-d-N4-hydroxycytidine (NHC), in the physiologically relevant HepaRG model. Toxicol. Res. 13, tfae012 (2024).
Honkoop, P., Scholte, H. R., de Man, R. A. & Schalm, S. W. Mitochondrial injury. Drug Saf. 17, 1–7 (1997).
Fenaux, M. et al. Antiviral nucleotide incorporation by recombinant human mitochondrial RNA polymerase is predictive of increased in vivo mitochondrial toxicity risk. Antimicrob. Agents Chemother. 60, 7077–7085 (2016).
Johnson, K. A. & Dangerfield, T. Mechanisms of inhibition of viral RNA replication by nucleotide analogs. Enzymes 49, 39–62 (2021).
Soldatow, V. Y., LeCluyse, E. L., Griffith, L. G. & Rusyn, I. In vitro models for liver toxicity testing. Toxicol. Res. 2, 23–39 (2012).
Schofield, C. A. et al. Evaluation of a three-dimensional primary human hepatocyte spheroid model: adoption and industrialization for the enhanced detection of drug-induced liver injury. Chem. Res. Toxicol. 34, 2485–2499 (2021).
Gough, A. et al. Human biomimetic liver microphysiology systems in drug development and precision medicine. Nat. Rev. Gastroenterol. 18, 252–268 (2021).
Hilpert, J. et al. Hepatotoxicity of AKR1C3 inhibitor BAY1128688: findings from an early terminated phase IIa trial for the treatment of endometriosis. Drugs R. D. 23, 221–237 (2023).
Howell, B. A. et al. In vitro to in vivo extrapolation and species response comparisons for drug-induced liver injury (DILI) using DILIsymTM: a mechanistic, mathematical model of DILI. J. Pharmacokinet. Pharmacodyn. 39, 527–541 (2012).
Shoda, L. K. M., Woodhead, J. L., Siler, S. Q., Watkins, P. B. & Howell, B. A. Linking physiology to toxicity using DILIsym®, a mechanistic mathematical model of drug‐induced liver injury. Biopharm. Drug Dispos. 35, 33–49 (2014).
Barrile, R. et al. Organ‐on‐chip recapitulates thrombosis induced by an anti‐CD154 monoclonal antibody: translational potential of advanced microengineered systems. Clin. Pharmacol. Ther. 104, 1240–1248 (2018).
Xie, J. H. et al. Engineering of a novel anti-CD40L domain antibody for treatment of autoimmune diseases. J. Immunol. 192, 4083–4092 (2014).
Nieskens, T. T. G. et al. Nephrotoxic antisense oligonucleotide SPC5001 induces kidney injury biomarkers in a proximal tubule-on-a-chip. Arch. Toxicol. 95, 2123–2136 (2021).
LaLone, C. A. et al. International consortium to advance cross‐species extrapolation of the effects of chemicals in regulatory toxicology. Environ. Toxicol. Chem. 40, 3226–3233 (2021).
InSphero. InSphero and pharmaceutical companies form pre-competitive consortium to advance development of in vitro tools to screen and predict drug-induced liver injury (DILI). https://insphero.com/x-species-consortium/ (2021).
Jang, K.-J. et al. Reproducing human and cross-species drug toxicities using a liver-chip. Sci. Transl. Med. 11, eaax5516 (2019).
European Union. Regulation (EC) No 1223/2009 of the European Parliament and of the Council of 30 November 2009 on cosmetic products (recast) (Text with EEA relevance)Text with EEA relevance. https://data.europa.eu/eli/reg/2009/1223/2022-12-17 (2022).
European Union. Regulation (EC) No 1907/2006 of the European Parliament and of the Council of 18 December 2006 concerning the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH), establishing a European Chemicals Agency, amending Directive 1999/45/EC and repealing Council Regulation (EEC) No 793/93 and Commission Regulation (EC) No 1488/94 as well as Council Directive 76/769/EEC and Commission Directives 91/155/EEC, 93/67/EEC, 93/105/EC and 2000/21/EC (Text with EEA relevance)Text with EEA relevance. https://data.europa.eu/eli/reg/2006/1907/2022-12-17 (2022).
Worth, A. P. & Patlewicz, G. Validation of alternative methods for toxicity testing. Adv. Exp. Med. Biol. 856, 317–342 (2016).
OECD. Guideline No. 497: defined approaches on skin sensitisation. OECD Guidelines for the Testing of Chemicals, Section 4. https://doi.org/10.1787/b92879a4-en (2021).
Delrue, N. et al. The adverse outcome pathway concept: a basis for developing regulatory decision-making tools. Altern. Lab. Anim. 44, 417–429 (2016).
Leist, M. et al. Adverse outcome pathways: opportunities, limitations and open questions. Arch. Toxicol. 91, 3477–3505 (2017).
Muller, P. Y. & Milton, M. N. The determination and interpretation of the therapeutic index in drug development. Nat. Rev. Drug Discov. 11, 751–761 (2012).
Naga, D., Parrott, N., Ecker, G. F. & Olivares-Morales, A. Evaluation of the success of high-throughput physiologically based pharmacokinetic (HT-PBPK) modeling predictions to inform early drug discovery. Mol. Pharm. 19, 2203–2216 (2022).
CNAM Working Group. Catalyzing the development and use of novel alternative methods. Report to the Advisory Committee to the NIH Director. https://acd.od.nih.gov/documents/presentations/Working_Group_Report.pdf (2023).
Baier, V. et al. A model‐based workflow to benchmark the clinical cholestasis risk of drugs. Clin. Pharmacol. Ther. 110, 1293–1301 (2021).
Haid, R. T. U. & Reichel, A. Transforming the discovery of targeted protein degraders: the translational power of predictive PK/PD modeling. Clin. Pharmacol. Ther. 116, 770–781 (2024).
Wu, F. et al. Computational approaches in preclinical studies on drug discovery and development. Front. Chem. 8, 726 (2020).
Watkins, P. B. DILIsym: quantitative systems toxicology impacting drug development. Curr. Opin. Toxicol. 23, 67–73 (2020).
Vamathevan, J. et al. Applications of machine learning in drug discovery and development. Nat. Rev. Drug Discov. 18, 463–477 (2019).
Dara, S., Dhamercherla, S., Jadav, S. S., Babu, C. M. & Ahsan, M. J. Machine learning in drug discovery: a review. Artif. Intell. Rev. 55, 1947–1999 (2022).
Oualikene-Gonin, W. et al. Artificial intelligence integration in the drug lifecycle and in regulatory science: policy implications, challenges and opportunities. Front. Pharmacol. 15, 1437167 (2024).
Ganesh, S. et al. Cytokine storm in a phase 1 trial of the anti-CD28 monoclonal antibody TGN1412. N. Engl. J. Med. 355, 1018–1028 (2006).
Vessillier, S. et al. Development of the first reference antibody panel for qualification and validation of cytokine release assay platforms—report of an International Collaborative Study. Cytokine X 2, 100042 (2020).
Hargrove-Grimes, P., Low, L. A. & Tagle, D. A. Microphysiological systems: stakeholder challenges to adoption in drug development. Cell Tissues Organs 211, 269–281 (2022).
Jensen, K. B. & Little, M. H. Organoids are not organs: sources of variation and misinformation in organoid biology. Stem Cell Rep. 18, 1255–1270 (2023).
Mohammadi, S. et al. Assessing donor-to-donor variability in human intestinal organoid cultures. Stem Cell Rep. 16, 2364–2378 (2021).
Zhao, Z. et al. Organoids. Nat. Rev. Methods Prim. 2, 94 (2022).
Zhou, C. et al. Standardization of organoid culture in cancer research. Cancer Med. 12, 14375–14386 (2023).
Kato, Y. et al. Analysis of reproducibility and robustness of OrganoPlate® 2-lane 96, a liver microphysiological system for studies of pharmacokinetics and toxicological assessment of drugs. Toxicol. Vitr. 85, 105464 (2022).
Lim, A. Y. et al. Reproducibility and robustness of a liver microphysiological system PhysioMimix LC12 under varying culture conditions and cell type combinations. Bioengineering 10, 1195 (2023).
NIH National Center for Advancing Translational Sciences. Tissue Chip Testing Centers. https://ncats.nih.gov/research/research-activities/tissue-chip/projects/centers (2016).
Rusyn, I. et al. Microphysiological systems evaluation: experience of TEX-VAL Tissue Chip Testing Consortium. Toxicol. Sci. 188, 143–152 (2022).
TissUse. Press release: Novel liver ring trial set to revolutionize drug safety assessment. https://www.tissuse.com/en/news/press-releases/ (2024).
Scannell, J. W. et al. Predictive validity in drug discovery: what it is, why it matters and how to improve it. Nat. Rev. Drug Discov. 21, 915–931 (2022).
Proctor, W. R. et al. Utility of spherical human liver microtissues for prediction of clinical drug-induced liver injury. Arch. Toxicol. 91, 2849–2863 (2017).
Fäs, L. et al. Physiological liver microtissue 384-well microplate system for preclinical hepatotoxicity assessment of therapeutic small molecule drugs. Toxicol. Sci. 203, 79–87 (2024).
Ewart, L. et al. Performance assessment and economic analysis of a human liver-chip for predictive toxicology. Commun. Med. 2, 154 (2022).
Congress, 118th. H.R.7248 - FDA Modernization Act 3.0. https://www.congress.gov/bill/118th-congress/house-bill/7248/text#:~:Text=To%20amend%20the%20Federal%20Food,product%20or%20other%20drug%2C%20and (2024).
Nelson, C. P. et al. Advancing alternative methods to reduce animal testing. Science 386, 724–726 (2024).
FDA. Potential approaches to drive future integration of new alternative methods for regulatory decision-making. https://www.fda.gov/media/182478/download?attachment (2024).
FDA. FDA’s ISTAND Pilot Program accepts a submission of first organ-on-a-chip technology designed to predict human drug-induced liver injury (DILI). https://www.fda.gov/drugs/drug-safety-and-availability/fdas-istand-pilot-program-accepts-submission-first-organ-chip-technology-designed-predict-human-drug (2024).
Ball, N. et al. A framework for chemical safety assessment incorporating new approach methodologies within REACH. Arch. Toxicol. 96, 743–766 (2022).
Baudy, A. R. et al. Liver microphysiological systems development guidelines for safety risk assessment in the pharmaceutical industry. Lab. Chip 20, 215–225 (2019).
Dalsbecker, P., Adiels, C. B. & Goksör, M. Liver-on-a-chip devices: the pros and cons of complexity. Am. J. Physiol. Gastrointest. Liver Physiol. 323, G188–G204 (2022).
Fu, J., Qiu, H. & Tan, C. S. Microfluidic liver-on-a-chip for preclinical drug discovery. Pharmaceutics 15, 1300 (2023).
Hassan, S. et al. Liver‐on‐a‐chip models of fatty liver disease. Hepatology 71, 733–740 (2020).
Yang, Z. et al. Liver-on-a-chip: considerations, advances, and beyond. Biomicrofluidics 16, 061502 (2022).
Vilas-Boas, V. et al. Primary hepatocytes and their cultures for the testing of drug-induced liver injury. Adv. Pharmacol. 85, 1–30 (2019).
Cho, S., Discher, D. E., Leong, K. W., Vunjak-Novakovic, G. & Wu, J. C. Challenges and opportunities for the next generation of cardiovascular tissue engineering. Nat. Methods 19, 1064–1071 (2022).
Jiao, Y.-C. et al. Advances in the differentiation of pluripotent stem cells into vascular cells. World J. Stem Cell 16, 137–150 (2024).
Roland, T. J. & Song, K. Advances in the generation of constructed cardiac tissue derived from induced pluripotent stem cells for disease modeling and therapeutic discovery. Cells 13, 250 (2024).
Pointon, A. et al. Cardiovascular microphysiological systems (CVMPS) for safety studies—a pharma perspective. Lab. Chip 21, 458–472 (2021).
Ashammakhi, N. et al. Gut-on-a-chip: current progress and future opportunities. Biomaterials 255, 120196 (2020).
Carvalho, M. R. et al. Gastrointestinal organs and organoids-on-a-chip: advances and translation into the clinics. Biofabrication 15, 042004 (2023).
McCoy, R. et al. In vitro models for investigating intestinal host–pathogen interactions. Adv. Sci. 11, 2306727 (2024).
Peters, M. F. et al. Developing in vitro assays to transform gastrointestinal safety assessment: potential for microphysiological systems. Lab. Chip 20, 1177–1190 (2020).
Yin, Y.-B., de Jonge, H. R., Wu, X. & Yin, Y.-L. Mini-gut: a promising model for drug development. Drug Discov. Today 24, 1784–1794 (2019).
Hoffmann, S. et al. Validation of an MPS based intestinal cell culture model for the evaluation of drug-induced toxicity. Front. Drug Discov. https://doi.org/10.3389/fddsv.2024.1459424 (2024).
Phillips, J. A. et al. A pharmaceutical industry perspective on microphysiological kidney systems for evaluation of safety for new therapies. Lab. Chip 20, 468–476 (2020).
Soo, J. Y.-C., Jansen, J., Masereeuw, R. & Little, M. H. Advances in predictive in vitro models of drug-induced nephrotoxicity. Nat. Rev. Nephrol. 14, 378–393 (2018).
Musah, S. et al. Mature induced-pluripotent-stem-cell-derived human podocytes reconstitute kidney glomerular-capillary-wall function on a chip. Nat. Biomed. Eng. 1, 0069 (2017).
Pașca, S. P. et al. A nomenclature consensus for nervous system organoids and assembloids. Nature 609, 907–910 (2022).
Rouleau, N., Murugan, N. J. & Kaplan, D. L. Functional bioengineered models of the central nervous system. Nat. Rev. Bioeng. 1, 252–270 (2023).
Kang, Y. J., Xue, Y., Shin, J. H. & Cho, H. Human mini-brains for reconstituting central nervous system disorders. Lab. Chip 23, 964–981 (2023).
Tan, H.-Y., Cho, H. & Lee, L. P. Human mini-brain models. Nat. Biomed. Eng. 5, 11–25 (2021).
De, A. et al. Lung-on-chip: its current and future perspective on pharmaceutical and biomedical applications. J. Drug Deliv. Sci. Technol. 78, 103930 (2022).
Lin, K.-C., Yen, C.-Z., Yang, J.-W., Chung, J. H. Y. & Chen, G.-Y. Airborne toxicological assessment: the potential of lung-on-a-chip as an alternative to animal testing. Mater. Today Adv. 14, 100216 (2022).
Francis, I. et al. Recent advances in lung-on-a-chip models. Drug Discov. Today 27, 2593–2602 (2022).
Ainslie, G. R. et al. Microphysiological lung models to evaluate the safety of new pharmaceutical modalities: a biopharmaceutical perspective. Lab. Chip 19, 3152–3161 (2019).
Lam, M., Lamanna, E., Organ, L., Donovan, C. & Bourke, J. E. Perspectives on precision cut lung slices—powerful tools for investigation of mechanisms and therapeutic targets in lung diseases. Front. Pharmacol. 14, 1162889 (2023).
Tomlinson, L. et al. Considerations from an International Regulatory and Pharmaceutical Industry (IQ MPS Affiliate) Workshop on the standardization of complex in vitro models in drug development. Adv. Biol. 8, e2300131 (2024).
Baran, S. W. et al. Perspectives on the evaluation and adoption of complex in vitro models in drug development: workshop with the FDA and the pharmaceutical industry (IQ MPS Affiliate). ALTEX 39, 297–314 (2022).
Stressor, D. M. et al. Towards in vitro models for reducing or replacing the use of animals in drug testing. Nat. Biomed. Eng. 8, 930–935 (2024).
Roth, A. Setting the scene—the investigative toxicology landscape in the European pharmaceutical industry. Toxicol. Lett. 280, S76 (2017).
Low, L. A., Mummery, C., Berridge, B. R., Austin, C. P. & Tagle, D. A. Organs-on-chips: into the next decade. Nat. Rev. Drug Discov. 20, 345–361 (2021).
Fabre, K. et al. Introduction to a manuscript series on the characterization and use of microphysiological systems (MPS) in pharmaceutical safety and ADME applications. Lab. Chip 20, 1049–1057 (2020).
Acknowledgements
The authors thank the European Federation of Pharmaceutical Industries and Associations (EFPIA)/Preclinical Development Expert Group (PDEG), especially P. Brinck, B. Haenen and E. Vock for initiating the establishment of this safety reflection working group.
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M.B., K.A., H.C.M.B., P.H., W.H., R.M., S.M., P.R., T.S.-H., R.V., T.v.V. are employees of pharmaceutical companies. R.V. holds equity in Emulate. The authors declare no further competing interests.
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3RsC: https://3rc.org/
ASPIS cluster: https://aspis-cluster.eu/
Biotechnology Innovation Organization: https://www.bio.org/
CleanCut: https://nc3rs.org.uk/crackit/cleancut
CrossDART: https://nc3rs.org.uk/crackit/crossdart
FDA news release in April 2025: https://www.fda.gov/news-events/press-announcements/fda-announces-plan-phase-out-animal-testing-requirement-monoclonal-antibodies-and-other-drugs
In vitro TDAR: https://nc3rs.org.uk/crackit/vitro-tdar
IQ Consortium: https://iqconsortium.org/
IQ MPS Afffiliate: https://www.iqmps.org/
NC3Rs: https://nc3rs.org.uk/
ONTOX: https://ontox-project.eu/
PrecisionTox: https://precisiontox.org/
Retinal 3D: https://nc3rs.org.uk/crackit/retinal-3d
Risk-Hunt3R: https://www.risk-hunt3r.eu/
SensOoChip: https://nc3rs.org.uk/crackit/sensoochip
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Beilmann, M., Adkins, K., Boonen, H.C.M. et al. Application of new approach methodologies for nonclinical safety assessment of drug candidates. Nat Rev Drug Discov 24, 705–725 (2025). https://doi.org/10.1038/s41573-025-01182-9
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DOI: https://doi.org/10.1038/s41573-025-01182-9