Table 4: Skills required for Pharma R&D Data Science44 A strong educational background. 88% of data scientists have a Master’s degree and 46% have PhDs


Collecting large amounts of structured and unstructured data and transforming it into a usable analytics-ready format

Solving business problems using data-driven techniques

Staying on top of analytical techniques such as machine learning, deep learning and text analytics, including benchmarking of methods


Domain Knowledge such as molecular biology, medicinal chemistry, clinical R&D, regulatory affairs, epidemiology, pharmaco-economics

Intellectual curiosity, creative problem-solving and strategic thinking

Relevant business acumen and awareness of industry trends


R Programming (43% of data scientists use R)

Medical statistics/pharmaceutical statistics45

Procedural and compiler coding Database query languages: SQL SPARQL Data modelling in relational and RDF form

Communicating and collaborating with both IT and the business

Looking for order and patterns in data, as well as spotting trends that generate value

Validating models and analyses

Communication skills to different levels of audience

Relationship-building, teamwork and conflict resolution

Understanding of legal, regulatory and ethical issues

Familiarity with cloud-based environments (AWS, Google, Microsoft)

Data visualisation techniques Machine Learning and AI

Text mining and related ontology use in semantic based text mining

In the early 2020s, many organisations suffered

delays in their R&D programmes due to a shortage of relevant skills. Today, the executive leadership of the biopharmaceutical industry has widely recognised the importance of the technology-biolo- gy interface to innovation. R&D IT – or R&D Technology as it has increasingly become known – is now seen as a strategic discipline and, important- ly, different from the traditional IT that supports line of business activities. Management has largely accepted that the rate

of change of the technology-science continuum is so rapid that extra effort has to be expended to keep the workforce’s skills up-to-date. As such, increased investment in training, development and education kept up-skilling personnel, allowing new technologies to be brought in without causing unnecessary redundancies in the workforce. Such training curricula were provided in large part by external organisations such as universities, eg Oxford University’s MSc in ‘Nanotechnology for Medicine and Health Care’37, or Harvard’s ‘CRISPR: Gene-editing Applications’38, or the Pistoia Alliance’s globally-recognised educational programmes,

including its member-driven ‘Technology Observatory’, which keeps members 46

up-to-date on emerging trends in life science and healthcare. In 2017, PhRMA commissioned a report

addressing efforts to attract and grow the biophar- maceutical industry39 and the availability of STEM skills. In 2018, the ABPI had produced a report entitled ‘Bridging the skills gap in the biopharma- ceutical industry’40. Digital experts needed to be encouraged to join

the biopharma industry and biopharma needed to compete against other industry sectors, such as the well-funded FinTech, as every company was fishing in the same limited talent pool. One of the key hur- dles to overcome in recruiting talented young peo- ple was the negative perception held by society of the biopharma industry, caused by many serious and on-going issues to do with transparency (for example Humphrey Rang’s review of Ben Goldacre’s book Bad Pharma: how drug compa- nies mislead doctors and harm patients41), and problems of pricing42. As highlighted in the PwC Pharma 2005, 2010

and 2020 reports, the perception that society had of the pharmaceutical industry continued to be very poor (see Table 3). Even today, the industry has still failed to grasp this fundamental problem

Drug Discovery World Winter 2019/20

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