Pharmacokinetics and Drug Metabolism

National Center For Advancing Translational Sciences

Investigators

Linked publications, trials & patents

Abstract

The DMPK group was established within the Therapeutic Development Branch in the Division of Preclinical Innovation (DPI) to address issues related to drug absorption, biodistribution and elimination via metabolism or excretion. The DMPK group has supported diverse projects across DPI, contributing significantly to all stages of translational research at NCATS, from early probe development in drug discovery to Phase II clinical trials. 1. In vitro ADME high-throughput screening (Tier I HTS assays) on solubility, permeability and microsomal stability for all small molecule compounds registered at NCATS (3000 compounds/year). 2. Customized in vitro ADME assays (Tier II assays) as required by each projects specific needs. The common Tier II assays include metabolic stability in different species, metabolite identification (MetID), aldehyde oxidase stability in cytosol fraction, plasma stability for prodrugs and biologics, blood/plasma partition, CYP inhibition, and transporter assessments in Caco-2 and MDKC cells. 3. PK studies in lab animals and bioanalytical measurements of drug concentrations in different biological fluids (e.g., blood, plasma, urine, bile) and tissue extracts. 4. UPLC-MS/MS and high-resolution accurate mass spectrometry for quantitation of small molecules and peptides, and structure identification of metabolites. 5. Bioanalytical method development for therapeutic macromolecules, such as recombinant human proteins and engineered proteins. 6. Pharmacokinetic parameter calculation and simulation. Scientific data generated from our lab have been used for novel target validations, ADME translational tools, repurposing approved drug for new indications, and research publications. Examples of the DMPK group contributions to recent projects within the Therapeutic Development Branch include: In Silico ADME Modeling: Characterization of in vitro ADME properties of a novel compound is very important in drug discovery research as it will guide structure optimization and lead selection. We have developed high-throughput assays for key ADME properties (Tier I ADME assays), such as aqueous solubility, membrane permeability and hepatic metabolic stability in microsomes. To date, we have collected data for approximately 30,000 compounds synthesized or registered at DPI/NCATS from Tier I ADME assays. We also collected data on thousands of compounds from Tier II assays (e.g. human CYP450 enzymes). To ensure data quality, we use controls in each plate and monitor the performance of these controls for all plates. We calculate Minimum Significant Ratio (MSR) for controls, a statistical parameter that characterizes the reproducibility of an assay, to evaluate assay performance. With high quality datasets in hand, we start to develop in silico models for these ADME properties. These in silico models are useful tools for medicinal chemists to design new drug-like molecules, which will potentially reduce the number of compounds to be synthesized during drug discovery, save valuable resources, minimize chemical wastes and ultimately help to accelerate the drug discovery process. The assay protocols for ADME Tier I and Tier II assays have been published in PubChem (see Table below, as of August 1, 2022), and the corresponding in silico models can be found at NCATS OpenData Portal: - Kinetic Aqueous Solubility; PubChem BioAssay AID: 1645848; https://opendata.ncats.nih.gov/adme/models/solubility - PAMPA Permeability (pH 7.4); PubChem BioAssay AID: 1508612; https://opendata.ncats.nih.gov/adme/models/pampa - PAMPA Permeability (pH 5); PubChem BioAssay AID: 1645871; https://opendata.ncats.nih.gov/adme/models/pampa - Tier I Rat Liver Microsome Stability; PubChem BioAssay AID: 1508591; https://opendata.ncats.nih.gov/adme/models/rlm - Mouse Cytosol Stability; PubChem BioAassay AID: 1508604 - Human Cytosol Stability; PubChem BioAssay AID: 1508603 - Human CYP3A4; PubChem BioAssay AID: 1645841; https://opendata.ncats.nih.gov/adme/models/cyp450 - Human CYP2C9; PubChem BioAssay AID: 1645842; https://opendata.ncats.nih.gov/adme/models/cyp450 - Human CYPY2D6; PubChem BioAssay AID: 1645840; https://opendata.ncats.nih.gov/adme/models/cyp450 Since the launch of our website on the In Silico ADME Models in 2021, we have exceeded 2000 registered users from more than 50 countries. In addition, three manuscripts are published on these in silico ADME models. Drug Discovery and Development for COVID-19 and Antiviral Program for Pandemics (APP): When COVID-19 outbreak occurred in early 2020, our lab responded quickly to this public health crises. We have worked on several drug discovery and development projects related to COVID-19 and APP: 1. Drug development for GS-441524, the parent drug of Remdesivir: In response to the public citizen letter on the proposal of developing orally administered anti-viral drug GS-441524, we conducted a series of in vitro ADME and in vivo PK studies in different species. Based on these in vitro and in vivo data, we simulated and predicted the human exposures after oral administration of GS-441524. All these data are used in the Investigational New Drug (IND) application with FDA. Our manuscript entitled Preclinical Pharmacokinetics and in vitro properties of GS-441524, a potential oral drug candidate for COVID-19 treatment has been accepted by the journal of Frontiers in Pharmacology. We also shared the data to public via NCATS OpenData Portal: https://opendata.ncats.nih.gov/covid19/GS-441524. 2. Application of In Silico ADME in drug discovery for antiviral drugs: As mentioned above, in silico ADME models could be used as powerful tools to accelerate drug discovery process. To illustrate its applications, we have been using these tools in our drug discovery projects, such as the discovery of SARS-CoV-2 PLpro inhibitors, a collaboration with Clear Creek Bio (CCB). We verified the models with CCB compounds that had experimental data, then predicted the ADME properties for newly designed molecules. By doing so, medicinal chemists could rank the newly designed molecules and give higher priority to the drug-like molecules in the synthesis drug the structure optimization process. We will continue such practice for other COVID-19 and APP projects.