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for cutting costs in drug development by predicting side effects early
The problem we tackle
The problem we tackle
90% of drugs fail in human trials, with 30% of them because of unforeseen side effects. This is an incredibly costly endeavor, since 1 failed drug costs $1 billion.
Our solution
Our solution
We believe that through more accurate computational models of disease we can pick better drug targets by predicting their side effects early.
This would then increase the success rate of all the following stages in the drug development pipeline.
Our models
Our models
Current computational methods for target identification:
Either have no long-term side-effect prediction (network-based, GEMs with the steady state)
assumption
Or are too unreliable for practical use (dynamical models based on equations derived by hand or based on weak data-driven methods)
Our breakthrough is creating the first system capable of highly accurate predictions
— with our exclusive EchoNet™ achieving a 90% improvement in accuracy over existing methods for dynamic metabolic modeling.
In the plots above, we see our system's performance on an open-source timeseries dataset of metabolic function, achieving dramatically better results that other available methods.
Target application
Target application
Our main focus is on partnerships with mid-to-large pharma in early R&D for Alzheimer’s disease
Current treatments cause brain bleeding as a side effect *
Central nervous system drugs require long safety windows and predictability of side effects — our system’s strength
Off-target effects and long-term metabolic impact are major reasons CNS drugs fail in trials — exactly the gap our models close
Other applications
Other applications
While our primary focus is revolutionizing drug development for Alzheimer's disease, our technology has powerful applications across multiple industries
Personalized Medicine
Personalized Medicine
Our biological modeling system can create patient-specific digital twins to optimize treatment plans based on individual physiological responses. This enables healthcare providers to tailor medication dosages, predict potential drug interactions, and minimize adverse effects while maximizing therapeutic outcomes—all before the patient takes their first dose.
Agricultural Optimization
Agricultural Optimization
By modeling plant metabolism and growth at unprecedented levels of detail, we can help agricultural companies develop more efficient fertilizers, predict crop responses to environmental stressors, and design sustainable pest management solutions. This reduces the need for extensive field testing while increasing crop yields and sustainability.
Biofuel Optimization
Biofuel Optimization
Our advanced biological modeling system transforms biofuel production by creating accurate digital twins of microbial metabolism and enzymes. This enables companies to refine growth conditions, boost conversion efficiency, and engineer better organisms through simulation instead of lengthy lab work. By forecasting the impact of genetic and environmental changes, we speed up next-gen sustainable fuel development while slashing R&D costs.
Partners
Partners
The innovations Griffin Labs brings to the target identification stage of drug discovery are uniquely positioned to address a critical bottleneck in pharmaceutical R&D — one that our BioAtomspace platform is also designed to complement and enhance
- Kennedy Schaal, CEO Rejuve Biotech
Contact
Contact
Reach us at info@griffinlabs.org
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