Data Scientist at Roche on generating business value, biggest challenges and great opportunities. An interview with Dr Mohammadjavad Faraji. - Big Data Technology Warsaw Summit
Can data science significantly generate medical and business value at a non-IT company like Roche?
Mohammadjavad Faraji [MF]: Definitely yes! The combined strengths of our pharmaceutical and diagnostic business under one roof already have made Roche the leader in personalised healthcare – PHC, offering comprehensive diagnostics and targeted therapies for people with cancer and other severe diseases. The digitalisation in healthcare now also brings the ability to understand and interpret unprecedented volumes of data that allows a higher resolution view of each individual patient than ever before. We are committed to delivering on this opportunity and are drawing on our unique combinations of strengths to drive this transformation. Our expertise in medicine, biology, diagnostics, data-science, our world-leading companies, such as Flatiron and Foundation Medicine, our partnerships, and our global reach will all contribute to that journey. Our aim is to transform our drug development, diagnostics, and care delivery so that we can deliver value to patients and the entire health care system.
In which area of product value chain do you see the biggest potential to apply data science and why?
[MF]: The transformative effects of using insights from data will have positive impacts along the entire value chain, translating to benefits for the whole healthcare ecosystem. Our focus spans from early science to product approval, to manufacturing, till the very end of the chain where we provide support for our products. It is certainly difficult to say in which area data science can play a bigger role – in terms of having bigger impact – because I see the entire value chain as one big area where data science is widely spread across its complementary components, with objectives such as validation of scientific hypotheses and deeper scientific insights, better, earlier go/no-go decisions in R&D, faster, more efficient trials, enhanced matching of patients and therapies, increasing access to therapies and effective maintenance of analyser instruments, etc.
What are the main challenges and opportunities of being a data scientist in a corporate world?
[MF]: I see great opportunities for data scientists to work in many different data science related areas within Roche, so there is plenty of choice. From a technical aspect, almost all different components of data science skill set are currently being used at Roche for addressing real challenges, including deep learning, natural language processing, predictive maintenance, etc. Delivering valuable insights as a result of combining those data science skills with domain knowledge, which will be acquired while working on different projects at Roche, is super exciting for any data scientist who is passionate about “doing now what patients need next”. Moreover, there is a very good sense of collaboration at Roche. As an example, we have an annual data science challenge where all data scientists at Roche across the globe work on one challenge, where they can do lots of exchange and self-development. Every challenge that a data scientist may face, while working on an initiative, is also an opportunity to learn something new. Without those challenges,