Harness the Potential of AI for Therapeutic Innovation in Life Sciences
As we’ve explained in many blogs and 5-minute guides, a cognitive search platform should combine AI technologies such as natural language processing, machine learning, and knowledge graphing to deliver a contextualized search and discovery experience without compromising security. Those technologies can turn ordinary search into something much more powerful and transformative for any organization. But in the hands of life sciences companies, it can help deliver drugs and other therapies that lessen suffering and save lives.
Cognitive Search Accelerates Therapeutic Innovation
Sometimes innovation doesn’t come in the form of a new drug. It comes in the form of a new use for drug that’s already received FDA approval. These “off-label” benefit patients, while increasing ROI for the company that created the drug. For example, Gabapentin, used primarily to treat seizures and neuropathic pain, is commonly prescribed for treating anxiety, insomnia, and bipolar disorder.
Cognitive search can help researchers confirm or reject an hypothesis about a potential new drug use by scouring internal and external data sources, including published medical literature, to confirm its value or abandon it. That highlights one of the primary features of a cognitive search platform.
A cognitive search platform should connect to, ingest, index, and analyze virtually any data type. That means having native connectors to scores of structured and unstructured data types residing in traditional relational databases and modern data frameworks such as Hadoop, NoSQL databases such as MongoDB and MarkLogic, columnar databases such as Apache Parquet, and data serialization engines like Apache AVRO. The platform should also include an SDK that allows developers to build connectors to new or proprietary data types.
The Path to Life Sciences Innovation Runs Through Mountains of Data
Any time someone wants to point to a data intensive industry, it’s usually financial services. But the life sciences are easily on par with financial services and probably exceed it. From published research in dozens of disciplines and clinical trial data to patent information, “voice of the patient” social media, and regulatory filings, life sciences companies take a back seat to no industry when it comes to data volume and diversity.
All that information holds enormous potential. But to foster innovation and shorten time to market, it must be harnessed. And that’s where cognitive search can deliver quantifiable results.
In this teaser for a Nov. 1 webinar, Mike Gualtieri, VP & Principal Analyst at Forrester Research, outlines several business drivers for AI-powered search in the life sciences.