Optimized Alectinib Dose Regimen for Treatment of Patients With ALK‐Positive Non‐Small Cell Lung Cancer Based on Robust Pharmacometric Analyses and Clinical Evidence

Model‐Informed Drug Development: Connecting the Dots With a Totality of Evidence Mindset to Advance Therapeutics

“…With advances in computational methods in pharmacometrics, it is envisioned that longitudinal models with mechanism‐informed frameworks will see greater adoption as they have the potential to enhance dose optimization and benefit/risk assessment. However, longitudinal time‐to‐event models necessitate additional important pharmacostatistical considerations, as cautioned by Frey et al ., who discuss the risks associated with immortal time bias, which if not accounted for appropriately, can lead to misleading apparent exposure–response relationships 19 . While landmark approaches may represent one solution, as pointed out by Groenland et al ., they do not account for dose reductions during treatment, introducing a different type of bias in estimating the underlying exposure–response relationships on longitudinal outcome data 20 .…”

“…However, longitudinal time-to-event models necessitate additional EDITORIAL important pharmacostatistical considerations, as cautioned by Frey et al, who discuss the risks associated with immortal time bias, which if not accounted for appropriately, can lead to misleading apparent exposure-response relationships. 19 While landmark approaches may represent one solution, as pointed out by Groenland et al, they do not account for dose reductions during treatment, introducing a different type of bias in estimating the underlying exposure-response relationships on longitudinal outcome data. 20 Finding the right balance of mechanistic appeal, statistical rigor, and pragmatism in exposure-response models to ultimately obtain credible answers to questions of clinical relevance will require close collaboration among clinical pharmacologists, systems pharmacologists, pharmacometricians, biostatisticians, and oncologists.…”

Toward Project Optimus for Oncology Precision Medicine: Multi‐Dimensional Dose Optimization Enabled by Quantitative Clinical Pharmacology

“…Clinical Pharmacology and Therapeutics ( CPT ) has been a home for research articles and reviews illustrating contemporary integrative approaches to inform dose selection of oncology therapeutics, including molecularly targeted small molecules, 5–7 immunotherapies, 8–11 antibody‐drug conjugates, 12–14 and cell therapies 15–17 . Several examples have catalyzed active scientific discussion contributing to growing appreciation of the biological complexity, population variability, and analytical methodology that demand careful consideration for robust dose optimization in oncology drug development 18–24 …”

“…[15][16][17] Several examples have catalyzed active scientific discussion contributing to growing appreciation of the biological complexity, population variability, and analytical methodology that demand careful consideration for robust dose optimization in oncology drug development. [18][19][20][21][22][23][24] In the current issue of CPT, Combes et al 25 illustrate the pivotal role of quantitative clinical pharmacology in optimizing dose selection for a molecularly targeted precision medicine in oncology through their study on asciminib, an allosteric inhibitor of BCR-ABL1 in chronic myeloid leukemia -chronic phase (CML-CP). Asciminib is active against wild-type BCR-ABL1 and several mutant forms of the kinase, including the T315I mutation, albeit with lower potency for T315I mutant BCR-ABL1 as established in cell proliferation assays in vitro, and in preclinical in vivo xenograft models using patient-derived CML cell lines.…”