Application of physiologically based pharmacokinetic modeling to predict drug disposition in pregnant populations.

Pregnancy is associated with numerous physiological changes that influence absorption, distribution, metabolism and excretion. Moreover, the magnitude of these effects changes as pregnancy matures. For most medications, there is limited information available about changes in drug disposition that can occur in pregnant patients, yet most women are prescribed one or more medications during pregnancy. In this investigation, PBPK modeling was used to assess the impact of pregnancy on the pharmacokinetic profiles of three medications (metformin, tacrolimus, oseltamivir) using the Simcyp® simulator. The Simcyp pregnancy-PBPK model accounts for the known physiological changes that occur during pregnancy. For each medication, plasma concentration-time profiles were simulated using Simcyp® virtual populations of healthy volunteers and pregnant patients. The predicted systemic exposure metrics (Cmax , AUC) were compared with published clinical data, and the fold error (FE, ratio of predicted and observed data) was calculated. The PBPK model was able to capture the observed changes in Cmax and AUC across each trimester of pregnancy compared with post-partum for metformin (FE range 0.86-1.19), tacrolimus (FE range 1.03-1.64) and oseltamivir (FE range 0.54-1.02). Simcyp model outputs were used to correlate these findings with pregnancy-induced alterations in renal blood flow (metformin, oseltamivir), hepatic CYP3A4 activity (tacrolimus) and reduced plasma protein levels and hemodilution (tacrolimus). The results illustrate how PBPK modeling can help to establish appropriate dosing guidelines for pregnant patients and to predict potential changes in systemic exposure during pregnancy for compounds undergoing clinical development.

Role of free radical in atherosclerosis, diabetes and dyslipidaemia: larger-than-life.

During the past few decades, there have been numerous studies related to free radical chemistry. Free radicals including reactive oxygen species (ROS) and reactive nitrogen species are generated by the human body by various endogenous systems, exposure to different physiochemical conditions, or pathological states, and have been implicated in the pathogenesis of many diseases. These free radicals are also the common by-products of many oxidative biochemical reactions in cells. When free radicals overwhelm the body's ability to regulate them, a condition known as oxidative stress ensues. They adversely alter lipids, proteins, and DNA, which trigger a number of human diseases. In a number of pathophysiological conditions, the delicate equilibrium between free radical production and antioxidant capability is distorted, leading to oxidative stress and increased tissue injury. ROS which are mainly produced by vascular cells are implicated as possible underlying pathogenic mechanisms in a progression of cardiovascular diseases including ischemic heart disease, atherosclerosis, cardiac arrhythmia, hypertension, and diabetes. This review summarizes the key roles played by free radicals in the pathogenesis of atherosclerosis, diabetes, and dyslipidaemia. Although not comprehensive, this review also provides a brief perspective on some of the current research being conducted in this area for a better understanding of the role free radicals play in the pathogenesis of atherosclerosis, diabetes, and dyslipidaemia.

Bridging the Gap With Clinical Pharmacology in Innovative Rare Disease Treatment Modalities: Targeting DNA to RNA to Protein.

Rare diseases are frequently caused by inherited 'monogenic' defects. Treatment interventions that target a specific genetic location or that replaces a specific protein provide rational therapeutic approaches. The current review discusses innovative targeted therapies that act or modulate at the level of DNA, RNA, or protein. They include DNA gene editing, small interference RNA (siRNA), antisense oligonucleotide (ASO), small molecule RNA splicing modifier, and bispecific antibody. With limited numbers of patients, testing multiple dose levels and regimens prior to making an informed dose decision remains one of the major challenges in rare disease drug development. Clinical pharmacology strategically bridges the gap to support drug development and regulatory approvals. Pharmacokinetic drug exposures are driven by absorption, distribution, metabolism, elimination, and in some cases immunogenicity. Drug responses are measured by pharmacodynamic biomarkers that are linked to either short- or long-term clinical outcomes. Understanding the drug exposure-response relationship lies at the heart of bridging the gap that enables a dose decision by balancing effectiveness and safety. Furthermore, and importantly, understanding the influence of intrinsic and extrinsic factors on drug pharmacokinetics enables dose adjustment decisions based on drug exposures. Case examples include the identification of doses and regimens without a formal dose-finding study, the support of new doses and regimens without conducting additional studies, and the extrapolation of adult drug-drug interaction (DDI) studies to pediatrics without performing a pediatric DDI study. With increasing discoveries of innovative treatment modalities, the responsibility of clinical pharmacologists is expected to grow and enhance the development of novel treatments for rare diseases.

A simplified PBPK modeling approach for prediction of pharmacokinetics of four primarily renally excreted and CYP3A metabolized compounds during pregnancy.

During pregnancy, a drug's pharmacokinetics may be altered and hence anticipation of potential systemic exposure changes is highly desirable. Physiologically based pharmacokinetics (PBPK) models have recently been used to influence clinical trial design or to facilitate regulatory interactions. Ideally, whole-body PBPK models can be used to predict a drug's systemic exposure in pregnant women based on major physiological changes which can impact drug clearance (i.e., in the kidney and liver) and distribution (i.e., adipose and fetoplacental unit). We described a simple and readily implementable multitissue/organ whole-body PBPK model with key pregnancy-related physiological parameters to characterize the PK of reference drugs (metformin, digoxin, midazolam, and emtricitabine) in pregnant women compared with the PK in nonpregnant or postpartum (PP) women. Physiological data related to changes in maternal body weight, tissue volume, cardiac output, renal function, blood flows, and cytochrome P450 activity were collected from the literature and incorporated into the structural PBPK model that describes HV or PP women PK data. Subsequently, the changes in exposure (area under the curve (AUC) and maximum concentration (C max)) in pregnant women were simulated. Model-simulated PK profiles were overall in agreement with observed data. The prediction fold error for C max and AUC ratio (pregnant vs. nonpregnant) was less than 1.3-fold, indicating that the pregnant PBPK model is useful. The utilization of this simplified model in drug development may aid in designing clinical studies to identify potential exposure changes in pregnant women a priori for compounds which are mainly eliminated renally or metabolized by CYP3A4.