Navigating Between Right, Wrong, and Relevant: The Use of Mathematical Modeling in Preclinical Decision Making

Cellular Kinetics and Biodistribution of Adoptive T Cell Therapies: from Biological Principles to Effects on Patient Outcomes

Cell-based immunotherapy has revolutionized cancer treatment in recent years and is rapidly expanding as one of the major therapeutic options in immuno-oncology. So far ten adoptive T cell therapies (TCTs) have been approved by the health authorities for cancer treatment, and they have shown remarkable anti-tumor efficacy with potent and durable responses. While adoptive T cell therapies have shown success in treating hematological malignancies, they are lagging behind in establishing promising efficacy in treating solid tumors, partially due to our incomplete understanding of the cellular kinetics (CK) and biodistribution (including tumoral penetration) of cell therapy products. Indeed, recent clinical studies have provided ample evidence that CK of TCTs can influence clinical outcomes in both hematological malignancies and solid tumors. In this review, we will discuss the current knowledge on the CK and biodistribution of anti-tumor TCTs. We will first describe the typical CK and biodistribution characteristics of these "living" drugs, and the biological factors that influence these characteristics. We will then review the relationships between CK and pharmacological responses of TCT, and potential strategies in enhancing the persistence and tumoral penetration of TCTs in the clinic. Finally, we will also summarize bioanalytical methods, preclinical in vitro and in vivo tools, and in silico modeling approaches used to assess the CK and biodistribution of TCTs.

Applying quantitative and systems pharmacology to drug development and beyond: An introduction to clinical pharmacologists

ABSTRACT

Quantitative and systems pharmacology (QSP) is an innovative and integrative approach combining physiology and pharmacology to accelerate medical research. This review focuses on QSP's pivotal role in drug development and its broader applications, introducing clinical pharmacologists/researchers to QSP's quantitative approach and the potential to enhance their practice and decision-making. The history of QSP adoption reveals its impact in diverse areas, including glucose regulation, oncology, autoimmune disease, and HIV treatment. By considering receptor-ligand interactions of various cell types, metabolic pathways, signaling networks, and disease biomarkers simultaneously, QSP provides a holistic understanding of interactions between the human body, diseases, and drugs. Integrating knowledge across multiple time and space scales enhances versatility, enabling insights into personalized responses and general trends. QSP consolidates vast data into robust mathematical models, predicting clinical trial outcomes and optimizing dosing based on preclinical data. QSP operates under a "learn and confirm paradigm," integrating experimental findings to generate testable hypotheses and refine them through precise experimental designs. An interdisciplinary collaboration involving expertise in pharmacology, biochemistry, genetics, mathematics, and medicine is vital. QSP's utility in drug development is demonstrated through integration in various stages, predicting drug responses, optimizing dosing, and evaluating combination therapies. Challenges exist in model complexity, communication, and peer review. Standardized workflows and evaluation methods ensure reliability and transparency.

A tutorial for model-based evaluation and translation of cardiovascular safety in preclinical trials

Assessment of drug-induced effects on the cardiovascular (CV) system remains a critical component of the drug discovery process enabling refinement of the therapeutic index. Predicting potential drug-related unintended CV effects in the preclinical stage is necessary for first-in-human dose selection and preclusion of adverse CV effects in the clinical stage. According to the current guidelines for small molecules, nonclinical CV safety assessment conducted via telemetry analyses should be included in the safety pharmacology core battery studies. However, the manual for quantitative evaluation of the CV safety signals in animals is available only for electrocardiogram parameters (i.e., QT interval assessment), not for hemodynamic parameters (i.e., heart rate, blood pressure, etc.). Various model-based approaches, including empirical pharmacokinetic-toxicodynamic analyses and systems pharmacology modeling could be used in the framework of telemetry data evaluation. In this tutorial, we provide a comprehensive workflow for the analysis of nonclinical CV safety on hemodynamic parameters with a sequential approach, highlight the challenges associated with the data, and propose respective solutions, complemented with a reproducible example. The work is aimed at helping researchers conduct model-based analyses of the CV safety in animals with subsequent translation of the effect to humans seamlessly and efficiently.

Delivering on the promise of protein degraders

Over the past 3 years, the first bivalent protein degraders intentionally designed for targeted protein degradation (TPD) have advanced to clinical trials, with an initial focus on established targets. Most of these clinical candidates are designed for oral administration, and many discovery efforts appear to be similarly focused. As we look towards the future, we propose that an oral-centric discovery paradigm will overly constrain the chemical designs that are considered and limit the potential to drug novel targets. In this Perspective, we summarize the current state of the bivalent degrader modality and propose three categories of degrader designs, based on their likely route of administration and requirement for drug delivery technologies. We then describe a vision for how parenteral drug delivery, implemented early in research and supported by pharmacokinetic-pharmacodynamic modelling, can enable exploration of a broader drug design space, expand the scope of accessible targets and deliver on the promise of protein degraders as a therapeutic modality.

A mechanistic PK/PD model to enable dose selection of the potent anti-tryptase antibody (MTPS9579A) in patients with moderate-to-severe asthma

Tryptase, a protease implicated in asthma pathology, is secreted from mast cells upon activation during an inflammatory allergic response. MTPS9579A is a novel monoclonal antibody that inhibits tryptase activity by irreversibly dissociating the active tetramer into inactive monomers. This study assessed the relationship between MTPS9579A concentrations in healthy subjects and tryptase levels in serum and nasal mucosal lining fluid from healthy subjects and patients with moderate-to-severe asthma. These data were used to develop a mechanistic pharmacokinetic/pharmacodynamic (PK/PD) model that quantitatively inter-relates MTPS9579A exposure and inhibition of active tryptase in the airway of patients with asthma. From initial estimates of airway tryptase levels and drug partitioning, the PK/PD model predicted almost complete neutralization of active tryptase in the airway of patients with asthma with MTPS9579A doses of 900 mg and greater, administered intravenously (i.v.) once every 4 weeks (q4w). Suppression of active tryptase during an asthma exacerbation event was also evaluated using the model by simulating the administration of MTPS9579A during a 100-fold increase in tryptase secretion in the local tissue. The PK/PD model predicted that 1800 mg MTPS9579A i.v. q4w results in 95.7% suppression of active tryptase at the steady-state trough concentration. Understanding how the exposure-response relationship of MTPS9579A in healthy subjects translates to patients with asthma is critical for future clinical studies assessing tryptase inhibition in the airway of patients with moderate-to-severe asthma.