Life Sciences
AI/ML and Virtual Reality in Drug Discovery
We are passionate innovators with a strong background in technology, AI/ML, and Virtual Reality, which has led us into the dynamic world of drug discovery. We identified gaps in current In Silico approaches and are working to improve them. Our goal is to collaborate closely with stakeholders in the drug discovery industry, leveraging advanced AI/ML techniques and immersive Virtual Reality (VR) experiences to make the drug discovery process faster, more efficient, and cost-effective.
In Silico Approaches in Drug Discovery
Traditional methods of drug discovery (X-ray crystallography, In Vivo, In Vitro) are time-consuming, costly, and sometimes biologically or chemically sub-optimal. AI/ML-based In Silico methods promise faster results, but existing processes face challenges due to the broad use of historical data. We focus on improving these approaches by:
▪ Data Optimisation: Narrowing the dataset to improve biological and chemical accuracy.
▪ Error Reduction: Avoiding the accumulation of errors from traditional approaches, which can affect AI/ML models.
▪ Cost Efficiency: Reducing failures by refining lead generation before clinical stages.
▪ Enhanced Precision: Especially effective in personalised medicine where relevant data leads to accurate results.
Our unique In Silico model addresses these challenges and optimizes the process, ensuring greater efficiency in drug discovery.
Virtual Reality in Drug Discovery
We harness VR to take the drug discovery process to an unprecedented level of interactivity and precision. The immersive 3D experience allows researchers to virtually step inside molecular structures, helping to:
▪ Molecular Visualisation: Explore complex molecular structures, enabling better understanding of drug-protein interactions.
▪ Collaborative Drug Design: Allow global teams to work together in shared virtual spaces, optimising drug candidates.
▪ Structure-Based Drug Design: Simulate and visualise the docking of small molecules into proteins, improving drug design.
Our unique In Silico model addresses these challenges and optimizes the process, ensuring greater efficiency in drug discovery.
Accelerated Drug Discovery
Faster identification of promising candidates
Improved Accuracy
AI-driven predictions enhance success rates
Cost Reduction
Optimize resources and reduce expenses
We are eager to collaborate with industry partners who are looking to overcome the current challenges in drug discovery through our AI/ML and VR-driven In Silico approaches.
