Too many new drug compounds fail in late-stage clinical trials due to inefficacy and safety concerns. With often-cited costs of $800 million to bring a new drug to market, a compelling need exists for improved early-stage screening. Insufficient knowledge of potential human toxicity can turn a promising lead candidate into a devastating loss. Emerging technologies that will change the existing paradigm were highlighted at Mondial Research Group’s recent conference on “Predictive Human Toxicity and ADME/Tox Studies (Absorption, Distribution, Metabolism, Elimination, and Toxicity)”.
“Every drug that fails in a clinical trial or after it reaches the market due to some adverse effect was ‘bad’ from the day it was first drawn by the chemist,” stated Robert Fraczkiewicz, Ph.D., team leader, ADMET cheminformatics at Simulations Plus. “Although state-of-the-art in silico structure-property prediction tools are not yet able to predict every possible toxicity for new molecular structures, they are able to predict many with good enough accuracy to eliminate poor molecules before synthesis.”
Just like humans with their individual characteristics such as age, weight, and height, calculated molecular descriptors (e.g., number of atoms, molecular weight, shape, and other parameters) quantitatively describe molecular structures.
Simulations Plus’ ADMET Predictor software mathematically correlates measured chemical-compound properties with their molecular descriptors to build predictive models. Currently, the application offers 133 predictive models and can process approximately 200,000 compounds per hour on a personal computer, Dr. Fraczkiewicz explained.
In silico usage is only widespread for a few select properties that have had long-time usage as primary indicators of potential new molecule druggability such as logP predictions (octanol-water partition coefficient), Dr. Fraczkiewicz noted. LogP predictions measure molecular hydrophobicity, which affects drug absorption, bioavailability, hydrophobic drug-receptor interactions, and may affect toxicity.
Current ionization, solubility, and permeability predictors range from simple equations to sophisticated, and quite accurate, artificial-neural-network ensembles such as the models implemented in ADMET Predictor, which are based on a combination of molecular and atomic quantum-level descriptors.
“Today, many in silico predictions have the same margin of error as their in vitro counterparts. We will not likely ever eliminate the need for in vitro or in vivo experiments for all molecules, but better in silico models can allow focusing the resources for these experiments where they are truly needed,” concluded Dr. Fraczkiewicz.
Obtaining Enough Primary Cells
Assays using primary cells, which represent in vivo physiology better than immortalized cell lines, can provide more accurate predictions of in vivo compound activity. “You can get false negatives and false positives from cell lines that are not primary cells,” advised Nicola Hewitt, Ph.D., scientific consultant, Medicyte.
Medicyte’s upcyte® technology addresses the major drawback in using primary cells for high-throughput-screening campaigns—that is, the difficulty in obtaining the needed number of cells.
“With our proprietary technology we identified genes that can induce and maintain proliferation of primary cells, circumventing the natural barrier points. Using a lentiviral gene-transfer system, we achieved effective transfer of these genes into human primary cells. These genetically engineered upregulated primary cells, termed upcytes, can be passaged for at least an additional 20 to 40 doublings. Up to 1,800 vials, containing 6 x 106 cells each, can be obtained from one vial of primary cells,” explained Dr. Hewitt.
With the ease-of-handling of cell lines, upcyte cells display the stable, normally differentiated phenotypes of primary cells. Cells from multiple donors provide experimental breadth early in the testing process.
Quality control consists of cell characterization at predetermined stages of proliferation. For example, upcyte hepatocytes are tested for expression of adult cell markers, the Dkk3/REIC gene (Reduced Expression in Immortalized Cells), glycogen storage, albumin and urea secretion, and inducible enzyme activity.
CYP3A4, one of the most important enzymes involved in the in vivo metabolism of xenobiotics, is a major target for many drug compounds. Inhibition of CYP3A4 by 10 mN ketoconazole decreases aflatoxin B1 toxicity similarly in primary cells and upcyte hepatocytes from multiple donors. Additional screening tests using compounds with a range of toxicity correlated well with in vivo hepatotoxicity.
Identifying Mitochondrial Liabilities
Thought to be responsible for 30 to 40% of previously undetected clinical tolerance problems resulting in cardiac and drug-induced liver injury (DILI), mitochondrial liability identification has become a prerequisite to IND submission for antivirals and is recommended by the FDA and the EMA for preclinical DILI anticipation.
“To identify mitochondrial liabilities with existing tests, you need four different screens using different models and different technologies with different sensitivities, which makes interpretation difficult and untranslatable site-to-site,” says Nathalie Compagnone, CEO, ICDD-sas.
“In addition, many existing tests use isolated mitochondria that respond to the experimental medium more than if they had the proper cellular environment. ICDD-sas carries out human in vitro systems using either biochemical or high-content analysis on live cells, and looks at the functional and dynamic response of mitochondrial to establish the toxicity liabilities of a drug.”
Mitosafe® is a series of mechanistic-based, preclinical-screening technologies that quantify bioenergetic balance, redox (reduction-oxidation), and mitochondrial DNA depletion statuses, the main biological aspects that a drug affects in the mitochondria. This balanced assay measures both anatomic and functional outcomes, identifying mitochondrial liabilities.
Inventors of the concept of mitochondrial behavior, ICDD-sas evaluates 48 parameters on living primary cells to quantify and qualify mitochondrial behavior. Adverse drug reactions can be forecast with 83% predictivity and >90% sensitivity and specificity.
The Mitostream technology, an experimental-system-biology predictive tool validated by the Drug Safety Executive Council and numerous pharmaceutical companies, is applied typically at the lead candidate level. Mitostream technology, which measures the cell adaptability in response to a drug, has proven effective in predicting clinical tolerance and is used for managing clinical trials.