Rescuing Failed Drug Trials
Unlock value from previous investments straight to the company bottom line
The best way to reverse a failed clinical trial
All pharmaceutical companies have many drugs that have failed in a previous clinical trial or were not approved by the FDA. Anywhere from $800M to $1.4B and many years have been spent on each compound. What if a percentage of these drugs or their derivatives could be brought to market? Imagine the benefit to patients with novel therapies that previously failed due to underlying genetic variants rendering them susceptible to adverse events. Unlock value from the previous investments straight to the company’s bottom line.
Most drug trials fail because of poor safety and efficacy
A vast majority of drug trials fail (86% of 406,000 trials)
A huge estimated national failed inventory exists (> $1T )
Poor efficacy and safety is, in part due to genetic variation
Trials can be redesigned using Heligenics' Mutation Effects on Gene Activity (MEGA-Maps™)
Mutation Effects on Gene Activity (MEGA-Maps™) – the solution for super-precision clinical trials to rescue failed trials
Convert a failed trial for a conventional drug to a successful super-precision clinical trial for a targeted therapy
Brivanib has had a massive investment and was tested for the treatment of patients with hepatocellular cancer in 25 different clinical trials and all trials have failed including four Phase 3 trials, the last in 2017 (clinicaltrials.gov). In general, the drug is well-tolerated but is failing trials for its poor efficacy, especially when compared to Sorafenib, the only approved drug on the market for this disease. The patient response to the drug is variable with some participants having a positive response and others with no effect.
The drug targets are 7 receptors in the tyrosine kinase family, three Vascular Endothelial Growth Factor Receptors 1-3 (VEGFR), and four Fibroblast Growth Factor Receptors 1-4 (FGFR). We took a closer look at one target VEGFR2 as an example. The structure for Brivanib complexed with a receptor was not available but there is a structure with another ATP analog, AAL993 that binds VEGFR2 (PDB: 5EW3). The contact residues for the drug with the binding site are V848, A866, V867, K868, I892, E885, I888, L889, V898, V914, V916, E917, C919, L1019, L1035, I1044, D1046, F1047.
There are no mutations in VEGFR2 for hepatocellular cancer and only 17 VEGFR2 variants for other disorders in ClinVar, the main public disease-variant database. However, there are 713 missense variants observed in ~250,000 people (GnomAD) ranging from singletons to 22% allele frequency; 74 variants are in the drug binding site region. There are about 1,500 missense variants observed in cancers (COSMIC), with approximately 100 in this binding site region.
Protein Databank structure of VEGFR2 bound to AAL993 (PDB: 5EW3)
Heligenics offers a new product to revitalize these failed drugs by stratifying genetically defined populations to enhance efficacy and safety, thus minimizing the main failure points for clinical trials. Through a massively parallel experimental test of the drug’s effect upon cells, Heligenics uses the “GigaAssay” to produce Mutation Effects on Gene Activity (MEGA-Maps™). Each MEGA-Map™ experiment measures the impact of all possible amino acid substitutions in the drug target upon the target’s molecular function. This experiment is repeated in the presence and absence of the drug.
To improve efficacy and safety, the comparison of MEGA-Maps™ identifies substitutions that can produce resistance, including those in the drug binding site, and those causing cell toxicity. The variants in the MEGA-Maps™ are next compared to population allele frequencies to identify the likelihood that patients with a deleterious variant could adversely impact a clinical trial. Clinical trials are redesigned with the knowledge of major alleles of the drug target that can produce resistance or toxicity as defined by the MEGA-Maps™. This knowledge is then used as exclusion criteria or arm stratification in a new trial or used retrospectively from existing data if genetic data were collected during the original trial. Alternatively, knowledge of amino acid positions associated with resistance or toxicity can guide drug derivatization or new drug development to reduce these important unwanted effects, thereby reducing risk in the drug development and approval process. Heligenics will test your custom drugs and targets which leads to increase safety and efficacy.