Immunetrics

Drug Discovery

Translating basic science in animal disease models to clinically relevant technology is a dismal prospect. By Phase III trials, many drugs have failed. The Immunetrics modeling technology can enhance a drug's potential for success at every stage of development. We provide insights that traditional development methods can't, shedding light on the most efficient path to FDA approval and beyond.

Lead selection and target identification

Immunetrics will help select clinical targets that change the trajectory of a patient's disease state. Because our models are built on real biological mechanisms, we can identify a system's "pressure points" – the effectors that, when perturbed, cause a meaningful change in the system. We point to targets ranging from intracellular species to serum biomarkers. The value of our technology is that we can predict whether a drug will perturb a "pressure point" enough to measurably alter a disease state in a target population of unlimited size, all without a real life clinical trial.

With recent technological developments, the availability of human genomic information has skyrocketed, and with it has come huge potential for contribution to the drug development process. The Immunetrics models can incorporate genetic data for use in a range of applications. We have extensive experience in modeling the effect of specific genes/SNPs on a drug's efficacy, and techniques to characterize the biological relevance of a newly-identified SNP by testing its function in our models.

Pre-clinical development

Because our models are based on the foundations of cellular and molecular interactions, we can tease out the details of a drug's mechanism of action. Research teams inevitably develop several hypotheses about mechanism or a drug's effect on its target. We can help identify the most likely scenario, and then suggest the best way to show experimentally why that scenario is most correct.

The Immunetrics team has invested considerable time and effort into creating a modeling infrastructure that allows for integration of data from all stages of drug development, from tissue culture to animals and humans. Why is this so important? Because we have such an infrastructure in place, our model will allow us to glean knowledge from this data that would otherwise be obscured by its diverse origins. For example, we can use animal data to estimate parameters specifically associated with a drug and its target. By transferring only these pieces of information to a human model, the differences between animals and humans can be generally accounted for, and we simulate the drug's effect in humans. It is through this method that we can use animal data to predict a drug's Phase II efficacy, preventing failure after lengthy and expensive clinical development.

Clinical development

Clinical trial design and analysis have historically been limited by inadequate knowledge regarding ideal dose and treatment regimen, small trial populations, and limited data collection. Immunetrics can enhance every aspect of the trial design process. We have used our modeling technology to devise inclusion/exclusion criteria, determine optimal trial size, predict trial variability, and identify high-responding patient groups. We take your existing trial data and generate large numbers of virtual patients, increasing statistical power and making it possible to test multiple doses and treatment regimens, while obtaining frequent, complete measurements throughout the entire trial. Simulated clinical trials can predict a "true treatment effect" by treating the same virtual patient with placebo and drug, and assess the role of genotype in drug treatment and response, a subtlety that real trials often overlook due to limited size.

Immunetrics also has extensive experience in pharmacokinetic modeling. We build mechanistic models of drug distribution down to the detail of metabolism by CYPs in the liver. Using these physiology-based pharmacokinetic models, we are able to predict a drug's PK/PD profile in individual patients with a range of comorbidities, accounting for concomitant medications and the presence of key genetic mutations.