Big data and artificial intelligence (AI) have the potential to improve clinical efficiency and drug discovery by decoding large data sets into actionable insights. Over the next two years, big data and AI will be the most disruptive influences in the pharma sector and will also be the areas where most investment is predicted to occur, according to GlobalData’s Digital Transformation and Emerging Technology in the Healthcare Industry report.

Pharma companies that neglect to implement big data and AI will be left behind by those who capitalize on the opportunities the technologies represent. However, the largest obstacle to digital transformation for pharma companies is the skills shortage. Pharma companies should therefore form strategic alliances with tech companies for expertise in order to strengthen their competencies in these technologies.

Go deeper with GlobalData

Data Insights

The gold standard of business intelligence.

Find out more

Related Company Profiles

View all

The best way to improve big data and AI competency is to partner with an established technology company.

Pharma companies will struggle to hire workers with AI expertise due to the high demand and low supply. Those qualified will likely seek employment at the big tech companies. Building in-house expertise could be time-consuming and expensive. Due to the complexity of the technology, incumbent employees lack the time and capabilities needed to become proficient with big data and AI. Traditional start-up acquisition is too risky, and the best option for pharma companies is to partner with established technology firms to ensure effective and reliable solutions.

Pharma companies are already recognising the opportunity Big Data and AI present

Big data and AI are already disrupting the pharma industry. The first drug developed by AI,DSP-1181, because of a partnership between Sumitomo Dainippon Pharma and British AI start-up Exscientia, has been tested on humans. The exploratory research phase took less than twelve months; on average, conventional research techniques take 4.5 years to do this. Exscientia estimates this can reduce the cost of drug development by over 30%.

How well do you really know your competitors?

Access the most comprehensive Company Profiles on the market, powered by GlobalData. Save hours of research. Gain competitive edge.

Company Profile – free sample

Thank you!

Your download email will arrive shortly

Not ready to buy yet? Download a free sample

We are confident about the unique quality of our Company Profiles. However, we want you to make the most beneficial decision for your business, so we offer a free sample that you can download by submitting the below form

By GlobalData
Visit our Privacy Policy for more information about our services, how we may use, process and share your personal data, including information of your rights in respect of your personal data and how you can unsubscribe from future marketing communications. Our services are intended for corporate subscribers and you warrant that the email address submitted is your corporate email address.

Additionally, Pharma titan GSK recently announced a partnership with NVIDIA to bolster the computational power of its new AI lab. NVIDIA is a computing solutions provider that specializes in graphics processing units but also offers processors, supercomputer software stacks and AI platforms. The lab will use AIto advance drug design and development.

In November 2020, Merck KGaA announced a collaboration with Itkos. Iktos’ AI technology, based on deep generative models, helps bring speed and efficiency to the drug discovery process, by automatically designing virtual novel molecules that have desired activities for treating a given disease.

Pharma companies cannot afford to forego the benefits of big data and AI. The ability to transform large data sets into practical, actionable insights represents a major opportunity to improve financial, operational, and clinical efficiency. Due to the difficulties entailed by other methods of implementation, strategic alliances with established technology firms are certainly the best option.