Drug-induced intestinal toxicity (GIT) is a frequent dose-limiting adverse event that can impact patient compliance and treatment outcomes. In vivo, there are proliferative and differentiated cell types critical to maintaining intestinal homeostasis. Traditional in vitro models using transformed cell lines do not capture this cellular complexity, and often fail to predict intestinal toxicity. Primary tissue-derived intestinal organoids, on the other hand, are a scalable Complex in vitro Model (CIVM) that recapitulates major intestinal cell lineages and function. Intestinal organoid toxicity assays have been shown to correlate with clinical incidence of drug-induced diarrhea, however existing studies do not consider how differentiation state of the organoids impacts assay readouts and predictivity. We employed distinct proliferative and differentiated organoid models of the small intestine to assess whether differentiation state alone can alter toxicity responses to small molecule compounds in cell viability assays. In doing so, we identified several examples of small molecules which elicit differential toxicity in proliferative and differentiated organoid models. This proof of concept highlights the need to consider which cell types are present in CIVMs, their differentiation state, and how this alters interpretation of toxicity assays.

Genotoxicity assays play a significant role in protecting clinical trial subjects from potential increased risk of genotoxic hazard and cancer during drug development. Traditional genetic toxicology assays typically provide binary outcomes with limited mechanistic insight. This study evaluates machine learning (ML) models based on an in-house implementation of MultiFlow DNA Damage Assay and MicroFlow Assays, and compared these results to previously published Litron assays. Our ML models demonstrated high accuracy, with MultiFlow data achieving 96% balanced accuracy for mode of action (MoA) prediction and 99% for genotoxicity prediction in repeated cross-validation. We collected and interpreted the MicroFlow and MultiFlow data in a dose–response format. The dose–response data enabled us to improve assay inference and model accuracy. In addition, we conducted case studies using toxicogenomic data, including the Toxicogenomic DNA Damage Inducing (TGx-DDI) transcriptomic biomarker and bulk RNA-seq, on a small set of compounds where the MoA is not clearly defined by MultiFlow or MicroFlow. The integration of toxicogenomics provided deeper insights into the molecular mechanisms of genotoxicity, allowing for the identification of specific pathways affected by these compounds. These findings emphasize the importance of careful endpoint selection and data interpretation. Overall, this study enhances the precision of genotoxicity predictions by integrating toxicogenomics, offering a framework for future genotoxicity safety assessments.

Modeling adaptive immune responses in induced pluripotent stem cell (iPSC)-derived liver systems remains a critical barrier for studying immune-mediated hepatic diseases, including idiosyncratic drug-induced liver injury (iDILI). Conventional hepatotoxicity models lack the components required to capture patient-specific, T cell-mediated injury. Here, a scalable and matrix-free human liver organoid (HLO) microarray platform is presented that enables controlled co-culture of Human Leukocyte Antigen (HLA)-genotyped, iPSC-derived HLOs with autologous CD8⁺ T cells. This immune-competent system supports antigen-specific T cell activation and reproduces cytotoxic effector responses in a genetically defined context. As a proof-of-concept, the platform models clinically relevant iDILI caused by flucloxacillin in HLA-B*57:01 carriers, recapitulating CD8⁺ T cell proliferation, hepatocyte apoptosis, and variability in immune responses across donors. The system captures hallmark features of adaptive immune-mediated hepatotoxicity, including secretion of tumor necrosis factor-alpha and Granzyme B, and cytokeratin-18 release from injured hepatocytes. By linking genetic susceptibility with functional immune outcomes, this platform provides a modular and scalable approach for evaluating immune-mediated toxicities. The method offers broad utility for mechanistic studies of drug hypersensitivity, immune-related adverse events, and preclinical safety assessment in support of precision medicine.

DILI (drug-induced liver injury) remains a critical liability in drug discovery and development. However, there are few in vitro and preclinical models to predict DILI, and the knowledge of DILI molecular targets is even more limited. The lapatinib (1) prescription label carries a black box warning for idiosyncratic hepatotoxicity and this has prompted numerous studies aimed at understanding the underlying molecular mechanisms. Using lapatinib as a tool molecule, we first identified a novel P450 3A5-catalyzed bioactivation, leading to highly reactive quinone methide (QM) metabolites formed after ortho- and para-hydroxylation at the 3F-benzyl ring, followed by self-immolation. The structure and activity relationship (SAR) studies of lapatinib analogs characterized the positional substitute-dependent quinone methide formation. Proteomics data revealed that quinone methide formation through bioactivation followed by simultaneous covalent modifications/functional disruption of several cellular enzymes in mitochondrial energy-production and reduction of oxidative stress could lead to mitochondrial stress and overall hepatotoxicity.

Next Generation Risk Assessment (NGRA) aims to improve safety testing of pharmaceuticals, agrochemicals, and industrial chemicals. NGRA employs new approach methodologies, such as novel in vitro assays coupled with exposure modeling, to minimize the use of animal models, which can fail to predict specific biological effects in humans. The strategy of the 'Omics for Assessing Signatures for Integrated Safety (OASIS) Consortium combines multi-omics technologies (including transcriptomics, proteomics, and Cell Painting [high-content imaging]) and multiple cell model systems (ranging from simple cell cultures to complex organotypic models). By integrating these approaches with internal exposure estimates, the consortium aims to improve the translation between in vitro and in vivo test systems, ultimately enhancing the relevance of safety assessment to human biology. OASIS's integrated approach aims to better translate the biological effects across different chemical and biological spaces, starting with the liver as a use case. By using compounds with well-characterized in vivo and in vitro nonclinical safety and toxicology data related to adverse organ-specific effects in rats and humans, OASIS aims to create novel integrated methods that improve safety assessment while reducing animal use. Ideally, these efforts will contribute to regulatory science across sectors and support the adoption of more predictive, efficient, and cost-effective toxicological models.

Genotoxicity assays play a significant role in protecting clinical trial subjects from potential increased risk of genotoxic hazard and cancer during drug development. Traditional genetic toxicology assays typically provide binary outcomes with limited mechanistic insight. This study evaluates machine learning (ML) models based on an in-house implementation of MultiFlow DNA Damage Assay and MicroFlow Assays, and compared these results to previously published Litron assays. Our ML models demonstrated high accuracy, with MultiFlow data achieving 96% balanced accuracy for mode of action (MoA) prediction and 99% for genotoxicity prediction in repeated cross-validation. We collected and interpreted the MicroFlow and MultiFlow data in a dose-response format. The dose-response data enabled us to improve assay inference and model accuracy. In addition, we conducted case studies using toxicogenomic data, including the Toxicogenomic DNA Damage Inducing (TGx-DDI) transcriptomic biomarker and bulk RNA-seq, on a small set of compounds where the MoA is not clearly defined by MultiFlow or MicroFlow. The integration of toxicogenomics provided deeper insights into the molecular mechanisms of genotoxicity, allowing for the identification of specific pathways affected by these compounds. These findings emphasize the importance of careful endpoint selection and data interpretation. Overall, this study enhances the precision of genotoxicity predictions by integrating toxicogenomics, offering a framework for future genotoxicity safety assessments.

Transient receptor potential ankyrin 1 (TRPA1) is a nonselective calcium ion channel highly expressed in the primary sensory neurons, functioning as a polymodal sensor for exogenous and endogenous stimuli, and has been implicated in neuropathic pain and respiratory disease. Herein, we describe the optimization of potent, selective, and orally bioavailable TRPA1 small molecule antagonists with strong in vivo target engagement in rodent models. Several lead molecules in preclinical single- and short-term repeat-dose toxicity studies exhibited profound prolongation of coagulation parameters. Based on a thorough investigative toxicology and clinical pathology analysis, anticoagulation effects in vivo are hypothesized to be manifested by a metabolite─generated by aldehyde oxidase (AO)─possessing a similar pharmacophore to known anticoagulants (i.e., coumarins, indandiones). Further optimization to block AO-mediated metabolism yielded compounds that ameliorated coagulation effects in vivo, resulting in the discovery and advancement of clinical candidate GDC-6599, currently in Phase II clinical trials for respiratory indications.

Pharmaceutical companies continue to advocate for the use of in vitro models towards the reduction of animal use in drug discovery and development while acknowledging that further advancements are needed to heighten the models’ current state of readiness.

Complex in vitro models (CIVM) offer the potential to improve pharmaceutical clinical drug attrition due to safety and/ or efficacy concerns. For this technology to have an impact, the establishment of robust characterization and qualifi­cation plans constructed around specific contexts of use (COU) is required. This article covers the output from a workshop between the Food and Drug Administration (FDA) and Innovation and Quality Microphysiological Systems (IQ MPS) Affiliate. The intent of the workshop was to understand how CIVM technologies are currently being applied by pharma­ceutical companies during drug development and are being tested at the FDA through various case studies in order to identify hurdles (real or perceived) to the adoption of microphysiological systems (MPS) technologies, and to address evaluation/qualification pathways for these technologies. Output from the workshop includes the alignment on a working definition of MPS, a detailed description of the eleven CIVM case studies presented at the workshop, in-depth analysis, and key take aways from breakout sessions on ADME (absorption, distribution, metabolism, and excretion), pharmacology, and safety that covered topics such as qualification and performance criteria, species differences and concordance, and how industry can overcome barriers to regulatory submission of CIVM data. In conclusion, IQ MPS Affiliate and FDA scientists were able to build a general consensus on the need for animal CIVMs for preclinical species to better determine species concordance. Furthermore, there was acceptance that CIVM technologies for use in ADME, pharmacology and safety assessment will require qualification, which will vary depending on the specific COU.

Despite the recent progress, multiple myeloma (MM) is still essentially incurable and there is a need for additional effective treatments with good tolerability. RO7297089 is a novel bispecific BCMA/CD16A-directed innate cell engager (ICE®) designed to induce BCMA+ MM cell lysis through high affinity binding of CD16A and retargeting of NK cell cytotoxicity and macrophage phagocytosis. Unlike conventional antibodies approved in MM, RO7297089 selectively targets CD16A with no binding of other Fcγ receptors, including CD16B on neutrophils, and irrespective of 158V/F polymorphism, and its activity is less affected by competing IgG suggesting activity in the presence of M-protein. Structural analysis revealed this is due to selective interaction with a single residue (Y140) uniquely present in CD16A opposite the Fc binding site. RO7297089 induced tumor cell killing more potently than conventional antibodies (wild-type and Fc-enhanced) and induced lysis of BCMA+ cells at very low effector-to-target ratios. Preclinical toxicology data suggested a favorable safety profile as in vitro cytokine release was minimal and no RO7297089-related mortalities or adverse events were observed in cynomolgus monkeys. These data suggest good tolerability and the potential of RO7297089 to be a novel effective treatment of MM patients.

Heterobifunctional compounds that direct the ubiquitination of intracellular proteins in a targeted manner via coopted ubiquitin ligases have enormous potential to transform the field of medicinal chemistry. These chimeric molecules, often termed proteolysis-targeting chimeras (PROTACs) in the chemical literature, enable the controlled degradation of specific proteins via their direction to the cellular proteasome. In this report, we describe the second phase of our research focused on exploring antibody-drug conjugates (ADCs), which incorporate BRD4-targeting chimeric degrader entities. We employ a new BRD4-binding fragment in the construction of the chimeric ADC payloads that is significantly more potent than the corresponding entity utilized in our initial studies. The resulting BRD4-degrader antibody conjugates exhibit potent and antigen-dependent BRD4 degradation and antiproliferation activities in cell-based experiments. Multiple ADCs bearing chimeric BRD4-degrader payloads also exhibit strong, antigen-dependent antitumor efficacy in mouse xenograft assessments that employ several different tumor models.

Abstract RO7297089 is a bispecific antibody (IgG-scFv) targeting Bcell maturation antigen (BCMA) and CD16a (FcγRIIIA) that is being developed for the treatment of multiple myeloma (MM). BCMA is exclusively expressed on plasmablasts and differentiated plasma cells (PCs), and is overexpressed on malignant PCs in MM patients. CD16a is expressed on natural killer (NK) cells, monocytes, mast cells, and macrophages. Herein, we characterized the mode of action and safety profile of RO7297089 in vitro and in vivo. RO7297089 showed potent cell killing when using BCMA+ MM tumor cell lines as target cells and human peripheral blood mononuclear cells, NK cells or macrophages as effector cells. Minimal increases in TNFα (2x) and IFNγ (4x), but not other cytokines/chemokines, were observed compared to the vehicle control treatment only in the presence of the BCMA+ MM tumor cell line up to the concentration tested. This suggests that, unlike T-cell engagers, the risk of cytokine release syndrome in patients receiving RO7297089 is low. Cynomolgus monkey is the only relevant nonclinical species for RO7297089 as it showed binding to both recombinant CD16 and BCMA with comparable affinity to human antigens. Following five weekly intravenous administrations to monkeys at 0, 15, and 50 mg/kg, RO7297089 was well tolerated. In line with the mechanism of action, there were no test article-related cytokine increases or adverse findings observed in both dose levels. Systemic exposure of RO7297089 was approximately dose proportional from 15 to 50 mg/kg. Anti-drug antibodies (ADA) were observed in some animals at both dose levels, and ADA-related decreases in concentrations were observed at only 15 mg/kg. To evaluate in vivo activity, RO7297089-related effects on total plasma sBCMA and PCs were assessed. Elevations of sBCMA levels (100x) were observed post dose at both dose levels, and these effects returned to predose levels in animals that did not maintain concentrations at 15 mg/kg, suggesting that RO7297089 bound to and stabilized circulating cynomolgus sBCMA. Time- and dose-dependent reductions in serum IgM levels were observed at both dose levels. Changes in PC numbers were not detected by immunophenotyping; however, gene expression analysis of PC markers was included and demonstrated clear reductions in mRNA expression levels of PC markers including BCMA and J-chain in blood at both dose levels, suggesting reductions in BCMA+ cells. Collectively, these studies suggest that RO7297089 selectively kills BCMA+ cells by engaging CD16a-positive immune cells and has a favorable safety profile. Citation Format: Satoko Kakiuchi-Kiyota, Melissa M. Schutten, Adeyemi O. Adedeji, Hao Cai, Robert Hendricks, Luna Liu, Sivan Cohen, Aaron M. Fullerton, Nicholas Corr, Lanlan Yu, Denise de Almeida Nagata, Shelly Zhong, Michael Dillon, Christoph Spiess, Steve R. Leong, Bing Zheng, Susanne Wingert, Uwe Reusch, Stefan Knackmuss, Thorsten Ross, Andrew Polson, Ayse M. Ovacik. Preclinical pharmacology and safety of RO7297089, a novel anti-BCMA/CD16a bispecific antibody for the treatment of multiple myeloma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4556.

Within the last 10 years, several tissue microphysiological systems (MPS) have been developed and characterized for retention of morphologic characteristics and specific gene/protein expression profiles from their natural in vivo state. Once developed, their utility is typically further tested by comparing responses to known toxic small-molecule pharmaceuticals in efforts to develop strategies for further toxicity testing of compounds under development. More recently, application of this technology in biopharmaceutical (large molecules) development is beginning to be more appreciated. In this review, we describe some of the advances made for tissue-specific MPS and outline the advantages and challenges of applying and further developing MPS technology in preclinical biopharmaceutical research.

Drug-induced liver injury (DILI) continues to be a major cause of drug attrition and restrictive labeling. Given the importance of farnesoid X receptor (FXR) in bile acid homeostasis, drug-related FXR antagonism may be an important mechanism of DILI. However, a comprehensive assessment of this phenomenon broadly in the context of DILI is lacking. As such, we used an orthogonal approach comprising a FXR target gene assay in primary human hepatocytes and a commercially available FXR reporter assay to investigate the potential FXR antagonistic effects of an extensive test set of 159 compounds with and without association with clinical DILI. Data were omitted from analysis based on the presence of cytotoxicity to minimize false positive assay signals and other complications in data interpretation. Based on the experimental approaches employed and corresponding data, the prevalence of FXR antagonism was relatively low across this broad DILI test set, with 16–24% prevalence based on individual assay results or combined signals in both assays. Moreover, FXR antagonism was not highly predictive for identifying clinically relevant hepatotoxicants retrospectively, where FXR antagonist classification alone had minimal to moderate predictive value as represented by positive and negative likelihood ratios of 2.24–3.84 and 0.72–0.85, respectively. The predictivity did not increase significantly when considering only compounds with high clinical exposure (maximal or efficacious plasma exposures > 1.0 μM). In contrast, modest gains in predictive value of FXR antagonism were observed considering compounds that also inhibit bile salt export pump. In addition, we have identified novel FXR antagonistic effects of well-studied hepatotoxic drugs, including bosentan, tolcapone and ritonavir. In conclusion, this work represents a comprehensive evaluation of FXR antagonism in the context of DILI, including its overall predictivity and challenges associated with detecting this phenomenon in vitro.

Myelosuppression is one of the most common and severe adverse events associated with anti-cancer therapies and can be a source of drug attrition. Current mathematical modeling methods for assessing cytopenia risk rely on indirect measurements of drug effects and primarily focus on single lineage responses to drugs. However, anti-cancer therapies have diverse mechanisms with varying degrees of effect across hematopoietic lineages. To improve predictive understanding of drug-induced myelosuppression, we developed a quantitative systems pharmacology (QSP) model of hematopoiesis in vitro for quantifying the effects of anti-cancer agents on multiple hematopoietic cell lineages. We calibrated the system parameters of the model to cell kinetics data without treatment and then validated the model by showing that the inferred mechanisms of anti-proliferation and/or cell-killing are consistent with the published mechanisms for three classes of drugs with different mechanisms of action. Using a set of compounds as a reference set, we then analyzed novel compounds to predict their mechanisms and magnitude of myelosuppression. Further, these quantitative mechanisms are valuable for the development of translational in vivo models to predict clinical cytopenia effects.