Energize precision medicine through biomarker discovery.
Pharmaceutical research is undergoing a massive change. Since the sequencing of the human genome in 2003, a vast and growing amount of molecular data is available, and a variety of computational methods are used for data analysis. Typically, this sort of molecular data in pure “omics” databases are structured and easily accessed.
Molecular level biomarkers and their relevance to the treatment of disease is the foundation of precision medicine. As an example, in cancer research biomarkers can answer questions like:
- Is this likely to develop into cancer?
- What form of cancer is it?
- What is the optimal drug and dose?
- Will the cancer return?
Unfortunately, a great deal of biomarker research data that could potentially be mined is not structured. The prime example is PubMed, the world’s premier medical database, which has over 24 million documents and grows at the rate of about a million records a year. That’s roughly two per minute, twenty-four hours a day. Other than some basic metadata like author and accession date, the PubMed system is entirely unstructured text.
The value of the PubMed database is awesome. But the size and growth make it essentially inaccessible to human researchers using manual techniques. For example, a simple keyword search in PubMed for “bladder cancer biomarker” yields well over seven thousand results.
Mining the PubMed database for biomarkers by efficiently and elegantly using natural language understanding can bring untold power to pharmaceutical and other biological sciences researchers.
Further, there exists countless correlations between papers; uncovering those correlations between disparate papers is the key to success.
MST’s powerful technology changes drug development from a “discovery” process to a targeted “design” process: the full potential of precision medicine is possible using our advanced natural language understanding.
MST’s ARE4 groundbreaking system offers a way to find, explore and comprehend biomarker relationships in medical data like never before possible. It’s a new tool for the promise of truly precision medicine.