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Big data a catalyst for computational predictive solutions enabling precision medicine: Taher Abbasi

Nandita Vijay, BengaluruWednesday, July 26, 2017, 08:00 Hrs  [IST]

Big data is a catalyst for computational predictive solutions enabling precision medicine. The key development in the area of precision medicine is to measure patient specific tumor attributes at reduced cost and faster turnaround time, said Taher Abbasi, COO & Co-Founder, Cellworks.

Generally, people are unaware about the right treatment and right approach for major diseases like cancer, tumor etc. The human cost of wrong treatments and economic cost of treatments leads to very expensive for an individual. In context of that health economics of adopting precision medicine products is very affordable. Hence the struggle is also against to remove the guesswork treatment, he added.

The significant achievement is at 85% and above accuracy of computer predictions with clinical response. Since 2005, when the company was incorporated in California, the company has developed products to apply use of patient attributes for precision medicine. Cellworks has two classes of products. One predicts the likelihood of response of treatment for a patient and the other is prediction of novel personalized treatments, Abbasi told Pharmabiz.

Healthcare industry is witnessing tremendous growth and evolving in its own way. It is challenging as for any emerging new technology area. These issues are compounded because multi-disciplinary skills of sciences, mathematics and computer engineering are much required.

Initiatives for early detection of disease conditions are ongoing across all disease conditions. The treatment personalization is mainly for cancer. “We are constantly exploring new opportunities both in the Indian and global market. Our future pathway is to establishing partnerships with clinical providers for a broader product deployment,” he said.

India is the company’s product development center site. This facility in Bengaluru which is an R&D centre develops the computational disease models and engineering workflows for creating digital models of patients for global partners. The technology validation is done by partners in the US. “We have also collaborations with healthcare institutions to test, develop and deploy products for enabling clinicians to make informed treatment decisions,” he said.

 
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