Points to Consider in Designing and Conducting Juvenile Toxicology Studies.

In support of a clinical trial in the pediatric population, available nonclinical and clinical data provide input on the study design and safety monitoring considerations. When the existing data are lacking to support the safety of the planned pediatric clinical trial, a juvenile animal toxicity study is likely required. Usually a single relevant species, preferably a rodent, is chosen as the species of choice, while a nonrodent species can be appropriate when scientifically justified. Juvenile toxicology studies, in general, are complicated both conceptually and logistically. Development in young animals is a continuous process with different organs maturing at different rates and time. Structural and functional maturational differences have been shown to affect drug safety. Key points to consider in conducting a juvenile toxicology study include a comparative development of the organ systems, differences in the pharmacokinetics/absorption, distribution, metabolism, excretion (PK/ADME) profiles of the drug between young animal and child, and logistical requirement in the juvenile study design. The purpose of this publication is to note pertinent points to consider when designing and conducting juvenile toxicology studies and to aid in future modifications and enhancements of these studies to enable a superior predictability of safety of medicines in the pediatric population.

Delayed-Release Dimethyl Fumarate and Pregnancy: Preclinical Studies and Pregnancy Outcomes from Clinical Trials and Postmarketing Experience.

INTRODUCTION: Delayed-release dimethyl fumarate (DMF; also known as gastro-resistant DMF) is an oral agent for the treatment of relapsing forms of multiple sclerosis (MS). No formal studies of DMF were conducted in pregnant women, although pregnancies have occurred during clinical trials and in the postmarketing setting. METHODS: Preclinical developmental and reproductive toxicology studies were performed with DMF in rats and rabbits. As of March 26, 2014, the DMF clinical development program included a total of 4132 subjects consisting of 2898 patients with MS, 320 psoriasis patients, 101 rheumatoid arthritis patients, and 813 healthy volunteers. Subjects were required to use reliable contraception and immediately discontinue treatment in the event of pregnancy. RESULTS: Animal studies showed no evidence of impaired fertility or teratogenicity with DMF. Overall as of June 30, 2014, 63 pregnancies were reported in clinical trials. Outcomes are known for 39 of 42 subjects receiving DMF and include 26 live births (67%), three spontaneous abortions (8%), and 10 elective terminations (26%); follow-up is ongoing in 2 cases and one patient was lost to follow-up. The incidence of spontaneous abortion in subjects exposed to DMF was consistent with the expected rate of early pregnancy loss in the general population (12-22%). A total of 135 pregnancies were reported in the postmarketing setting (spontaneous and solicited reports). Outcomes are known for 30 cases and include 10 live births, 13 spontaneous abortions, and 5 elective terminations; follow-up is ongoing in 103 cases and 2 patients have been lost to follow-up. CONCLUSION: Although data are limited and all known exposures have occurred in the first trimester, no increased risk of fetal abnormalities or adverse pregnancy outcomes associated with gestational exposure to DMF has been observed. FUNDING: Biogen, Inc.

In silico prediction of hERG inhibition.

The voltage-gated potassium channel encoded by hERG carries a delayed rectifying potassium current (IKr) underlying repolarization of the cardiac action potential. Pharmacological blockade of the hERG channel results in slowed repolarization and therefore prolongation of action potential duration and an increase in the QT interval as measured on an electrocardiogram. Those are possible to cause sudden death, leading to the withdrawals of many drugs, which is the reason for hERG screening. Computational in silico prediction models provide a rapid, economic way to screen compounds during early drug discovery. In this review, hERG prediction models are classified as 2D and 3D quantitative structure-activity relationship models, pharmacophore models, classification models, and structure based models (using homology models of hERG).