Clinical pharmacology provides insights about optimal drug exposure at site of action to maximize efficacy and safety in patients. Throughout all stages of drug development, critical decisions pertaining to drug administration including dosing regimen and route of administration are supported by clinical pharmacology. Alimentiv clinical pharmacology experts can provide insights to those important questions related to the pharmacokinetic (PK) and pharmacodynamic (PD) properties of both small and large molecules (biologics).
Characterization of the absorption, distribution, metabolization and elimination of a compound are critical to describe early on during drug development. Non-compartmental PK analyses can provide rapid insights, allowing a precise description of a drug PK profile in healthy subjects and/or patients. Our team at Alimentiv has the expertise to perform non-compartmental PK analysis of drug exposure in serum, stool, and colonic mucosal tissue biopsies in early and late phases of drug development.
In particular for biologics, substantial inter- and intra-individual variation in drug exposure and response pose significant challenges to early drug development. Population PK and PK-PD modelling enables the characterization of the dose-exposure and exposure-response relationships of drugs to understand which covariates may explain part of the observed variability. Models are typically constructed using sparse data on systemic/tissue drug concentrations, dosing information, patient demographics, disease characteristics and clinical, endoscopic, histopathologic, or molecular outcomes collected from either clinical trial or real-world datasets. These models can account for intra- and inter- subject variability of drug exposure resulting from predictable patient demographic or disease factors or non-predictable random effects. As these factors may change over time, it is important that the model takes into account the time-varying nature of these covariates (Vande Casteele et al., 2017).
PK and PKPD models are powerful tools to support critical data-driven decisions in early drug development as they can simulate drug exposure and response to different dosing regimens in either a population of similar patients, or in a population of patients with different disease and demographic characteristics. Population PK models can predict drug exposure and these predicted values can be used to conduct multivariable logistic regression modeling for exposure-response analysis.
Our pharmacometrics team at Alimentiv can develop population PK and PKPD models for both small and large molecules (biologics) and support model-informed development of your drug to optimize dosing and facilitate a personalized medicine approach.
Optimization and selection of the optimal dosing regimen associated with drug efficacy and safety in patients is a critical step in early drug development. Using population models, PK and PKPD profiles can be simulated for different dosing regimen scenarios applied to a typical patient population, or to a population of patients with a specific disease or demographic characteristics. Our team can help you make data-driven decisions through model-based simulations to accelerate drug development.
Ensuring therapeutic exposure to increase probability of patients attaining optimal efficacy and safety responses from drug therapy is a priority for drugs in clinical development or even in clinical practice. Therapeutic drug monitoring with measurement of drug concentrations (and anti-drug antibody concentrations in the case of biologics) provides an opportunity to assess in individual patients whether drug exposure is optimal. To enable such a personalized medical approach, it is essential to determine systemic drug exposure thresholds associated with response and to identify patient disease or demographic factors that influence response to drug therapy (Vande Casteele et al., 2018).
Exposure-response analysis explores the association of drug exposure in serum, stool, and colonic mucosal tissue biopsies with clinical, endoscopic, histopathologic, and molecular outcomes. The effects of covariates that may influence the exposure-response association are assessed by multivariable logistic regression modelling.
Our team at Alimentiv has wide experience in drug exposure-response analyses, including the development of dosing calculators that are designed to provide support to prescribers for personalized drug therapy (Vande Casteele et al., 2020).