Classification of Companion Diagnostics: A New Framework for Biomarker-Driven Patient Selection

A quantitative systems pharmacology workflow toward optimal design and biomarker stratification of atopic dermatitis clinical trials

BACKGROUND

The development of atopic dermatitis (AD) drugs is challenged by many disease phenotypes and trial design options, which are hard to explore experimentally.

OBJECTIVE

We aimed to optimize AD trial design using simulations.

METHODS

We constructed a quantitative systems pharmacology model of AD and standard of care (SoC) treatments and generated a phenotypically diverse virtual population whose parameter distribution was derived from known relationships between AD biomarkers and disease severity and calibrated using disease severity evolution under SoC regimens.

RESULTS

We applied this workflow to the immunomodulator OM-85, currently being investigated for its potential use in AD, and calibrated the investigational treatment model with the efficacy profile of an existing trial (thereby enriching it with plausible marker levels and dynamics). We assessed the sensitivity of trial outcomes to trial protocol and found that for this particular example the choice of end point is more important than the choice of dosing regimen and patient selection by model-based responder enrichment could increase the expected effect size. A global sensitivity analysis revealed that only a limited subset of baseline biomarkers is needed to predict the drug response of the full virtual population.

CONCLUSIONS

This AD quantitative systems pharmacology workflow built around knowledge of marker-severity relationships as well as SoC efficacy can be tailored to specific development cases to optimize several trial protocol parameters and biomarker stratification and therefore has promise to become a powerful model-informed AD drug development and personalized medicine tool.

MiRNAs as potential therapeutic targets and biomarkers for non-traumatic intracerebral hemorrhage

Non-traumatic intracerebral hemorrhage (ICH) is the most common type of hemorrhagic stroke, most often occurring between the ages of 45 and 60. Hypertension is most often the cause of ICH. Less often, atherosclerosis, blood diseases, inflammatory changes in cerebral vessels, intoxication, vitamin deficiencies, and other reasons cause hemorrhages. Cerebral hemorrhage can occur by diapedesis or as a result of a ruptured vessel. This very dangerous disease is difficult to treat, requires surgery and can lead to disability or death. MicroRNAs (miRNAs) are a class of non-coding RNAs (about 18-22 nucleotides) that are involved in a variety of biological processes including cell differentiation, proliferation, apoptosis, etc., through gene repression. A growing number of studies have demonstrated miRNAs deregulation in various cardiovascular diseases, including ICH. In addition, given that computed tomography (CT) and/or magnetic resonance imaging (MRI) are either not available or do not show clear signs of possible vessel rupture, accurate and reliable analysis of circulating miRNAs in biological fluids can help in early diagnosis for prevention of ICH and prognosis patient outcome after hemorrhage. In this review, we highlight the up-to-date findings on the deregulated miRNAs in ICH, and the potential use of miRNAs in clinical settings, such as therapeutic targets and non-invasive diagnostic/prognostic biomarker tools.