The Utility of a Population Approach in Drug-Drug Interaction Assessments: A Simulation Evaluation

An Investigation in the Comparability of the Exposure and Recommended Dose of Selected Pfizer Drugs in East Asian Countries: Is Mutual Usage of Clinical Data Among East Asian Countries Feasible?

The current regulatory path for new drug registration in East Asian countries has led to significant delay of the new medicines in these countries. A unified regulatory path and allowance of mutual usage of clinical data in East Asian countries would lead to cost saving in drug development and expedite the new drug registration in these countries. The objectives of the present analysis are to compare the approval dates of a selection of products developed by Pfizer in the United States and East Asian countries (China, Japan, Korea) and compare the pharmacokinetics and recommended doses of these products in East Asian countries. Eighteen products (20 drugs, 2 products with 2 combination drugs) with exposure data available in at least 2 of the 3 East Asian countries across different therapeutic areas were included in the analyses. The results showed that most products had delayed approval in East Asian countries (up to 8 years) after US or EU approval. No distinct differences were observed in the drug exposure and recommended doses for the selected products in East Asian countries. These results together with literature data of genetic similarity of the East Asian populations support the mutual usage of the clinical data in the East Asian countries for expedited regulatory submission and approval.

Therapeutic Protein Drug Interactions: A White Paper From the International Consortium for Innovation and Quality in Pharmaceutical Development

Typically, therapeutic proteins (TPs) have a low risk for eliciting meaningful drug interactions (DIs). However, there are select instances where TP drug interactions (TP-DIs) of clinical concern can occur. This white paper discusses the various types of TP-DIs involving mechanisms such as changes in disease state, target-mediated drug disposition, neonatal Fc receptor (FcRn), or antidrug antibodies formation. The nature of TP drug interaction being investigated should determine whether the examination is conducted as a standalone TP-DI study in healthy participants, in patients, or assessed via population pharmacokinetic analysis. DIs involving antibody-drug conjugates are discussed briefly, but the primary focus here will be DIs involving cytokine modulation. Cytokine modulation can occur directly by certain TPs, or indirectly due to moderate to severe inflammation, infection, or injury. Disease states that have been shown to result in indirect disease-DIs that are clinically meaningful have been listed (i.e., typically a twofold change in the systemic exposure of a coadministered sensitive cytochrome P450 substrate drug). Type of disease and severity of inflammation should be the primary drivers for risk assessment for disease-DIs. While more clinical inflammatory marker data needs to be collected, the use of two or more clinical inflammatory markers (such as C-reactive protein, albumin, or interleukin 6) may help broadly categorize whether the predicted magnitude of inflammatory disease-DI risk is negligible, weak, or moderate to strong. Based on current knowledge, clinical DI studies are not necessary for all TPs, and should no longer be conducted in certain disease patient populations such as psoriasis, which do not have sufficient systemic inflammation to cause a meaningful indirect disease-DI.

Analysis of US Food and Drug Administration Oncology Approvals on the Characterization of Hepatic Impairment Effect and Dosing Recommendations

Patients with cancer and advanced hepatic impairment (HI) (i.e., moderate and severe impairment) are often excluded from first-in-patient, phase II, and phase III studies. Thus, dose recommendations for this subgroup of patients are often derived using a combination of dedicated phase I studies conducted in participants without cancer and a population pharmacokinetic (PK) modeling approach. A standardized risk-based approach to guide the evaluation of HI in patients with cancer is needed. In this review, we evaluated available oncology drug approvals by the US Food and Drug Administration (FDA) from 1999 to 2019, identified strategies utilized by sponsors to characterize the effect of HI on the PK of oncology drugs, and assessed regulatory expectations for each strategy. Finally, we constructed a decision tree that complements current FDA guidance to enable efficient evaluation of the effect of HI on PK and provide guidance for dose recommendations.

Pediatric Drug-Drug Interaction Evaluation: Drug, Patient Population, and Methodological Considerations

Hospitalized pediatric patients and those with complex or chronic conditions treated on an outpatient basis are commonly prescribed multiple drugs, resulting in increased risk for drug-drug interactions (DDIs). Although dedicated DDI evaluations are routinely performed in healthy adult volunteers during drug development, they are rarely performed in pediatric patients because of ethical, logistical, and methodological challenges. In the absence of pediatric DDI evaluations, adult DDI data are often extrapolated to pediatric patients. However, the magnitude of a DDI in pediatric patients may differ from adults because of age-dependent physiological changes that can impact drug disposition or response and because of other factors related to the drug (eg, dose, formulation) and the patient population (eg, disease state, obesity). Therefore, the DDI magnitude needs to be assessed in children separately from adults, although a lack of clinical DDI data in pediatric populations makes this evaluation challenging. As a result, pediatric DDI assessment relies on the predictive performance of the pharmacometric approaches used, such as population and physiologically based pharmacokinetic modeling. Therefore, careful consideration needs to be given to adequately account for the age-dependent physiological changes in these models to build high confidence for such untested DDI scenarios. This review article summarizes the key considerations related to the drug, patient population, and methodology, and how they can impact DDI evaluation in the pediatric population.

Matrix Effects of the Hydroethanolic Extract of Calyces of Physalis peruviana L. on Rutin Pharmacokinetics in Wistar Rats Using Population Modeling

Rutin is the rutinose conjugate of quercetin. It presents several biological activities and is the major flavonoid in the hydroalcoholic extract of the calyces of Physalis peruviana L. It also shows hypoglycemic activity after oral administration. The aim of this work was to study the matrix effects of the extract from P. peruviana calyces on the pharmacokinetics of rutin and its metabolites in Wistar rats, using non-compartmental and population pharmacokinetic analyses. A pharmacokinetic study was performed after intravenous and oral administration of different doses of pure rutin and the extract. In the non-compartmental analysis, it was found that rutin from the extract exhibited higher distribution and clearance, as well as an 11-fold increase in the bioavailability of its active metabolites. A population pharmacokinetic model was also carried out with two compartments, double absorption and linear elimination, in which the extract and the doses were the covariates involved. This model correctly described the differences observed between rutin as a pure compound and rutin from the extract, including the dose dependency.

Clinical Studies on Drug-Drug Interactions Involving Metabolism and Transport: Methodology, Pitfalls, and Interpretation

Many drug-drug interactions (DDIs) are based on alterations of the plasma concentrations of a victim drug due to another drug causing inhibition and/or induction of the metabolism or transporter-mediated disposition of the victim drug. In the worst case, such interactions cause more than tenfold increases or decreases in victim drug exposure, with potentially life-threatening consequences. There has been tremendous progress in the predictability and modeling of DDIs. Accordingly, the combination of modeling approaches and clinical studies is the current mainstay in evaluation of the pharmacokinetic DDI risks of drugs. In this paper, we focus on the methodology of clinical studies on DDIs involving drug metabolism or transport. We specifically present considerations related to general DDI study designs, recommended enzyme and transporter index substrates and inhibitors, pharmacogenetic perspectives, index drug cocktails, endogenous substrates, limited sampling strategies, physiologically-based pharmacokinetic modeling, complex DDIs, methodological pitfalls, and interpretation of DDI information.