This Biotech Startup Is Using AI To Help Researchers Develop Cures Quicker Posted on : Aug 20 - 2017

The increased use of artificial intelligence and machine learning is steadily shifting the paradigm of medical research and treatment, providing researchers real-time access to every white paper and clinical case study conducted on a genetic disorder. Being able to develop such an elaborate database of information allows researchers to not only understand the full scope of a medical condition, but further shorten the amount of time it takes to develop a cure.

Founded in 2011, Innoplexus is a technology and product development company focused on solving complex challenges in the pharmaceutical and life sciences industries. Their end-to-end platform for Life Sciences research uses artificial intelligence to generate smart data and insights to assist in the discovery, clinical development and regulatory compliance of pharmaceutical medicine.

On a mission to create self-service products that help enhance decision-making, their platform compiles hundreds of terabytes worth of scientific information spread across clinical trial databases, biological databases, major patent offices, forums and regulatory bodies.

In addition to strengthening research efforts, Innoplexus works to help life science and healthcare organizations leverage these technologies to improve care. Whether a drug developer is seeking existing research, a medical researcher is searching for alternative treatments, or a practitioner is attempting to find data on a particular disease -- increasing access to relevant information removes roadblocks to discovery and fuels rapid growth.

I spoke with Co-Founder Guarav Tripathi about the vision behind Innoplexus, disrupting the medical research industry, and how artificial intelligence is defining the future of modern medicine.

What was the specific void or opportunity you saw that inspired the idea behind Innoplexus?

Gaurav Tripathi: Most of the information the life sciences industry relied on was based on an outdated data and analytics consulting model. Essentially, data was collected and curated manually, and then sold at high premium to clients. This kind of information may be helpful in some industries, but when it comes to research-heavy fields like pharmaceutical development and medical research, experts need more current and comprehensive data assets. Our response was to bring an automated Data as a Service (DaaS) model, which makes the data available seamlessly in rea- time. We also built an Analytics as a Service model to deliver continuous and custom insights for the industry in a way that was previously unattainable. Such insights that make data more useful for supporting decisions were not available on a continual basis. Where they were available, it was often in time-consuming batches that required immense amounts of manual effort. Since industries pertaining to our health move at a fast pace, the speed at which you can access and analyze data is critical. View More