Over the past few weeks, we’ve explored the technology disrupting the life sciences industry, looking at how big data and cloud platforms are changing, stimulating and accelerating the sector.
In the final of our disruptive technologies blog series, we’re dissecting artificial intelligence in life sciences - examining the power of AI and the opportunities ahead for candidates and clients.
How artificial intelligence is transforming the life sciences
Artificial intelligence is the science of building technology capable of performing complex tasks that typically require human intelligence. For a sector under increasing cost and productivity pressures, and bursting at the seams with unstructured data, AI is an exciting concept.
Life sciences companies are developing and adopting AI at record rates, as shown by a forecast CAGR of 29.42% between 2020 - 2025. The principal areas AI is transforming are:
Artificial intelligence is leading to faster diagnostics. Intelligent algorithms analyse complex datasets and images to diagnose conditions far quicker than a practitioner can manually. Not only is this leading to earlier treatments and better patient outcomes, but it’s also curbing the “Google effect,” where nearly two in five people misdiagnose themselves with a more serious condition after looking up their symptoms on Google - often resulting in unnecessary urgent care visits.
For example, Buoy Health’s AI chatbot leads 32% of users to reduce the urgency of their intended level of care.
Life sciences companies using AI in manufacturing are experiencing enhanced productivity and increased cost efficiencies - leading to faster drug development. Artificial intelligence automates data management, scans and cross-references complex datasets, and forecasts demand at record speed.
Last year bioinformatics company, Insilico Medicine, used AI to design, synthesis and validate a novel drug candidate in 46 days - 15 times faster than leading pharma companies.
AI is also transforming clinical research by analysing medical records and cross-referencing trials to identify patients suitable for clinical research, far quicker than traditional methods.
For example, LA-start-up Deep 6 AI’s patient qualification tool helped Cedars-Sinai Medical Center identify 16 patients suitable for a trial in 30 minutes. Eight patients were recruited in just three weeks - far quicker than previous trials, where two patients were recruited in six months.
Artificial intelligence technologies are helping food production companies make better decisions to improve production and product success.
For example, Trace Genomics are able to extract DNA from soil to analyse its microbial community and generate recommendations for maximizing soil health and improving crop yield. Spoonshot’s Concept Generator uses AI to predict the types of food different combinations of raw ingredients and compounds will produce, allowing companies to develop an entire product virtually before deciding which products to physically prototype.
The challenges of AI for life sciences
The potential of AI in the life sciences is huge for companies and clients. Those embracing the technology now will gain competitive early mover advantage. However, certain challenges are holding the industry back.
If you caught the first of our disruptive technologies blog series, you know the life sciences have lagged a little in the big data movement. Access to data is the biggest barrier to adoption of AI in the life sciences, with data gaps and inaccessible data prevent AI from working.
Further reading: How Data is Transforming the Life Sciences
A lack of skills is the second biggest barrier to AI adoption in life sciences. Tech companies are luring the top AI talent with attractive benefits and perks, making AI specialists a limited resource in the life sciences sector. Companies must have a robust recruitment strategy for finding technical talent and attracting it to the life sciences field.
Katherine Andiole, PhD, Center for Clinical Data Science, describes AI development as a “team sport”. For AI to work you must involve a variety of stakeholders, including machine learning experts, clinicians and data scientists. AI isn’t just a technology investment - it’s an investment in different people, talents and insights, and this is leading to many different collaborations.
For example, this year we saw George Okafo, former global head of GlaxoSmithKline’s computer-aided drug discovery unit, take on the role as program lead for Insilico Medicines’ six-month AI sprint, aimed at finding new treatments for brain cancer.
This collaboration between life sciences and AI experts is being fostered by platforms such as Legit, that allow enterprise AI companies to identify and connect with life sciences experts.
Finally, some candidates and companies are scared of AI, with misconceived perceptions that artificial intelligence is taking over jobs and removing the human element. However, AI is here to enhance jobs and propel the sector forward. For example, AI could create new life sciences business, such as digital-based elder care.
How Panda International can help
The AI life sciences market is worth $1,101.1 million, and experts predict this figure to quadruple by 2025. It’s clear AI is becoming a strategic priority for many life sciences companies, so how can Panda International help you take advantage?
At Panda International, we hold the latest insights into the life sciences industry, allowing you to recruit strategically for the future.
We work closely with the best candidates in the industry, giving you access to a wide pool of life sciences talent.
We work with world-leading companies in the life sciences sector and have a variety of career-enhancing opportunities for your life sciences career.
Our dedicated and specialised recruitment consultants partner with you to bring the best results now and in the future - whatever technology it holds.