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Effects of genetic variants on the risk of complex diseases estimated from association studies are typically small. Nonetheless, variants may have important effects in presence of specific levels of environmental exposures, and when a trait related to the disease (endophenotype) is either normal or impaired. We propose polytomous and transition models to represent the relationship between disease, endophenotype, genotype and environmental exposure in family studies. Model coefficients were estimated using generalized estimating equations and were used to derive gene-environment interaction effects and genotype effects at specific levels of exposure. In a simulation study, estimates of the effect of a genetic variant were substantially higher when both an endophenotype and an environmental exposure modifying the variant effect were taken into account, particularly under transition models, compared to the alternative of ignoring the endophenotype. Illustration of the proposed modeling with the metabolic syndrome, abdominal obesity, physical activity and polymorphisms in the NOX3 gene in the Quebec Family Study revealed that the positive association of the A allele of rs1375713 with the metabolic syndrome at high levels of physical activity was only detectable in subjects without abdominal obesity, illustrating the importance of taking into account the abdominal obesity endophenotype in this analysis.

We extend the usual logistic model between a dichotomous phenotype and an allele count in two ways: a polytomous phenotype with K > 2 levels, and modelling of allele counts at two unlinked marker loci. Inference is based on within-family information to guard against potential bias due to population genetic structure. Score tests of the model coefficients taking into account the correlation between relatives in entire pedigrees are derived as an extension of the Generalized Disequilibrium Test (GDT). Simulations confirm that the tests have the expected statistical properties, and that their power exceeds that of the GDT under a favorable scenario. The score tests are illustrated with candidate genetic markers, a major psychosis phenotype and a cognitive endophenotype in large kindreds from Eastern Quebec.

What Is This Summary About?: In this article, we summarize results from a clinical study called LOTIS-2, in which researchers looked at patients with a type of blood cancer called diffuse large B-cell lymphoma, or DLBCL for short. Patients received the drug loncastuximab tesirine, or Lonca for short, which targets a marker on the surface of tumor cells called CD19.Patient information from the LOTIS-2 study, other studies of Lonca, and information from scientific publications was used to develop a quantitative systems pharmacology (QSP) model, which can predict how Lonca works in the body. The goal was to use the QSP model to see if CD19 levels can predict tumor size changes after Lonca treatment and if Lonca can still work to treat DLBCL when CD19 levels are very low. The prior LOTIS-1 and LOTIS-2 trials demonstrated an acceptable safety profile for Lonca, and therefore the current study did not evaluate safety data., What Were the Results?: Researchers used immunohistochemistry, a common technique to evaluate CD19 expression. They found that there was no association between patients who responded to Lonca treatment and levels of CD19 on their tumor cells. Some patients with low or even undetectable levels of CD19 on their tumor cells had observable decreases in tumor size after Lonca treatment., What Do the Results of the Study Mean?: While Lonca uses the CD19 target to find and destroy cancer cells, Lonca does not require a large amount of CD19 to kill tumor cells. These results mean that Lonca may be an effective treatment for patients with DLBCL, even if CD19 expression in tumors is undetectable by immunohistochemistry.

CD19-targeting treatments have shown promise in relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL). Loncastuximab tesirine (loncastuximab tesirine-lpyl [Lonca]) is a CD19-targeting antibody-drug conjugate indicated for R/R DLBCL after at least two systemic treatments. CD19 expression was evaluated in patients receiving Lonca in the LOTIS-2 clinical trial with available tissue samples obtained after last systemic therapy/before Lonca treatment. Lonca cytotoxicity was evaluated in a panel of six lymphoma cell lines with various CD19 expression levels. Quantitative systems pharmacology (QSP) modelling was used to predict Lonca responses. Lonca responses were seen in patients across all CD19 expression levels, including patients with low/no detectable CD19 expression and H-scores at baseline. Similarly, Lonca induced cytotoxicity in cell lines with different levels of CD19 expression, including one with very low expression. QSP modelling predicted that CD19 expression by immunohistochemistry alone does not predict Lonca response, whereas inclusion of CD19 surface density improved response prediction. Virtual patients responded to Lonca with estimated CD19 as low as 1000 molecules/cell of CD19, normally below the immunohistochemistry detection level. We found Lonca is an effective treatment for R/R DLBCL regardless of CD19 expression by immunohistochemistry. These results provide the basis for future studies addressing CD19-targeted agent sequencing., Competing Interests: PFC was on the advisory board for ADC Therapeutics SA, Amgen, BeiGene, Bristol Myers Squibb (BMS), Genentech, Kite, MEI Pharmaceuticals and Novartis and received research funding from AbbVie, ADC Therapeutics SA, and Genentech. MH has been a consultant with AbbVie, ADC Therapeutics SA, BMS, Caribou, CRISPR, Gamida Cell, Genmab, Incyte Corporation, Kadmon, Kite, Legend Biotech, MorphoSys, Novartis, Omeros and Seagen; received research funding from ADC Therapeutics SA and Spectrum Pharmaceuticals; has speakers bureau memberships for ADC Therapeutics SA, AstraZeneca, BeiGene, Kite, and Sanofi Genzyme and participated on data monitoring committees for Genentech and Myeloid Therapeutics. CC‐S has been a consultant with Sanofi; has been on the board of directors, speakers bureau or advisory committee for ADC Therapeutics SA, BMS, Celgene, Karyopharm, Roche and Sanofi; has received research funding from ADC Therapeutics SA, Roche and Sanofi and has received honoraria from ADC Therapeutics SA, AstraZeneca, BMS, Incyte, Janssen Oncology, and Takeda. MN is currently employed at Boehringer Ingelheim Pharmaceuticals, Inc. EJ was an employee of Metrum Research Group at the time of the study. KU and TK are currently employed at Metrum Research Group. FZ and YW were employees of ADC Therapeutics SA, a publicaly traded company, at the time of the study and may hold stock. DC, SP and JB are currently employed and current stockholders at ADC Therapeutics SA, a publicly traded company. KH is currently employed and a current stockholder at ADC Therapeutics (UK) Ltd, a publicly traded company. ETHICS STATEMENTThe authors have confirmed an ethical approval statement is not needed for this submission., (© 2023 The Authors. eJHaem published by British Society for Haematology and John Wiley & Sons Ltd.)

Physiologically-based pharmacokinetic (PBPK) models are mechanistic models that are built based on an investigator's prior knowledge of the in vivo system of interest. Bayesian inference incorporates an investigator's prior knowledge of parameters while using the data to update this knowledge. As such, Bayesian tools are well-suited to infer PBPK model parameters using the strong prior knowledge available while quantifying the uncertainty on these parameters. This tutorial demonstrates a full population Bayesian PBPK analysis framework using R/Stan/Torsten and Julia/SciML/Turing.jl., (© 2023 Metrum Research Group and The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The 21 st Century Cures Act requires FDA to expand its use of real-world evidence (RWE) to support approval of previously approved drugs for new disease indications and post-marketing study requirements. To address this need in neonates, the FDA and the Critical Path Institute (C-Path) established the International Neonatal Consortium (INC) to advance regulatory science and expedite neonatal drug development. FDA recently provided funding for INC to generate RWE to support regulatory decision making in neonatal drug development. One study is focused on developing a validated definition of bronchopulmonary dysplasia (BPD) in neonates. BPD is difficult to diagnose with diverse disease trajectories and few viable treatment options. Despite intense research efforts, limited understanding of the underlying disease pathobiology and disease projection continues in the context of a computable phenotype. It will be important to determine if: 1) a large, multisource aggregation of real-world data (RWD) will allow identification of validated risk factors and surrogate endpoints for BPD, and 2) the inclusion of these simulations will identify risk factors and surrogate endpoints for studies to prevent or treat BPD and its related long-term complications. The overall goal is to develop qualified, fit-for-purpose disease progression models which facilitate credible trial simulations while quantitatively capturing mechanistic relationships relevant for disease progression and the development of future treatments. The extent to which neonatal RWD can inform these models is unknown and its appropriateness cannot be guaranteed. A component of this approach is the critical evaluation of the various RWD sources for context-of use (COU)-driven models. The present manuscript defines a landscape of the data including targeted literature searches and solicitation of neonatal RWD sources from international stakeholders; analysis plans to develop a family of models of BPD in neonates, leveraging previous clinical trial experience and real-world patient data is also described., Competing Interests: TK, JB, and EJ were employed by the Metrum Research Group. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Barrett, Cala Pane, Knab, Roddy, Beusmans, Jordie, Singh, Davis, Romero, Padula, Thebaud and Turner.)

Neutralizing monoclonal antibodies (mAb), novel therapeutics for the treatment of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), have been urgently researched from the start of the pandemic. The selection of the optimal mAb candidate and therapeutic dose were expedited using open-access in silico models. The maximally effective therapeutic mAb dose was determined through two approaches; both expanded on innovative, open-science initiatives. A physiologically-based pharmacokinetic (PBPK) model, incorporating physicochemical properties predictive of mAb clearance and tissue distribution, was used to estimate mAb exposure that maintained concentrations above 90% inhibitory concentration of in vitro neutralization in lung tissue for up to 4 weeks in 90% of patients. To achieve fastest viral clearance following onset of symptoms, a longitudinal SARS-CoV-2 viral dynamic model was applied to estimate viral clearance as a function of drug concentration and dose. The PBPK model-based approach suggested that a clinical dose between 175 and 500 mg of bamlanivimab would maintain target mAb concentrations in the lung tissue over 28 days in 90% of patients. The viral dynamic model suggested a 700 mg dose would achieve maximum viral elimination. Taken together, the first-in-human trial (NCT04411628) conservatively proceeded with a starting therapeutic dose of 700 mg and escalated to higher doses to evaluate the upper limit of safety and tolerability. Availability of open-access codes and application of novel in silico model-based approaches supported the selection of bamlanivimab and identified the lowest dose evaluated in this study that was expected to result in the maximum therapeutic effect before the first-in-human clinical trial., (© 2021 Eli Lilly and Company. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)