Artificial Intelligence in Life Science — Demystifying the Buzz

Artificial Intelligence in Life Science — Demystifying the Buzz

This article was originally published to Bruno’s LinkedIn.

The Biotechnology Innovation Organization held its annual convention digitally this year, as part of which I had the opportunity to join the panel, “Demystifying Buzzwords – How Artificial Intelligence and Machine Learning are being used Now in the Life Sciences” with esteemed professionals [1] from all corners of the biotechnology industry.

The discussion is well-timed. Over the past decade we have seen the convergence of massive data sets, near-unlimited computing power, and advanced data science. The most pioneering biotechnology companies have moved beyond the hype. They now use AI and ML to turbo-charge efficiencypower up knowledge, and cut time from data to evidence.

Turbo-Charge Efficiency

AI does more than making a biotechnician’s job easier. The ability to analyze a torrent of data and relate it to tricky questions and challenges allows us to reach new depths and heights. AI and ML broaden our horizons as well. We might all need to become data scientists at some point to leverage the wealth of opportunities.

AI and ML serves as a “force multiplier” as Krishnan Nandabalan described it. After hitting a bottleneck back in 2015, InveniAI started using AI and ML to automate steps which led them to improved efficiency and enhanced analytical capabilities. Similarly, at Centrexion, AI and ML helped Kerrie Brady and the team to “bite big and chew hard” so even as a team of 6, they were able to manage five development projects.

When AI and ML apply to every part of the value chain, these technologies can promote efficiency, effectiveness, and increase probability of success. At Novartis, we are embedding AI and ML across the drug development value chain. We have many initiatives to maximize the value of these technologies to make sure they are not just widespread but also have depth.

Power Up Knowledge

Some professionals think that AI doesn’t just stand for Artificial Intelligence — it is an Accelerator of Innovation. In describing this technology, Moira Gunn said, “There’s no doubt about it; once you’re able to grasp it and put it to work, it accelerates innovation as we know it. That’s brand new, and that’s one of the reasons that our whole industry could change. Not from a test tube, but from data and from information.”

Some also define AI as Augmented Intelligence. AI doesn’t exist and operate in a vacuum; humans are critical to assess the reliability of the input and output, and synthesize collected data further. Aashish Kachru addressed this symbiotic relationship and advised us to “Embrace the job displacement that’s going to come as a result of AI, and move yourself towards higher skill values where you’ll be needed.”

The current global pandemic creates one such circumstance in which higher skill values are necessary. COVID-19 has led to a great deal of renewed connectivity and openness across the pharma industry. Technology such as Natural Language Processing has enabled this effort, scanning millions of publications and tapping into global knowledge to answer an individual team’s questions. An individualistic line of thinking is far too narrow when it comes to AI and ML. The panel highlighted the opportunity to refine the life sciences ecosystem, allowing companies to leverage their strengths and pool decentralized knowledge, as it can help individuals and healthcare professionals make the best informed decisions.

Cut Time from Data to Evidence

Novartis’ data42 program applies advanced analytics to derive medical insights from 2 million patient-years of data. We have primarily focused on bringing that data together and making it AI and ML-ready. These insights contribute to our increasing understanding of diseases and medicine, thereby enhancing R&D decision-making and ultimately #reimagining drug discovery and development by cutting the time from data to evidence.

But it all started with data. This is the condition for knowledge-workers really to be knowledge-workers, as opposed to data janitors and information engineers, creating room for operational, analytical, and experiential value growth, thereby expanding our capabilities.

According to multiple analyses, it can take over a decade to bring a new drug to patients, and only one out of ten drugs is successful. Early AI and ML opportunities have shown the potential to cut years off this timeline and maximize the probability of success. For which, as several panelists pointed out, making AI and ML part of the value chain end-to-end is the key.

Conclusion

The hype that AI and ML are disrupting the way we work is true, to an extent. AI and ML lead to reduced company costs and improved customer experiences, while Price Waterhouse Coopers reports that AI alone is expected to have a $15.7 trillion economic impact by 2030.

Completely in line with Brian Martin stating that “we have moved from myth to value”. As he elaborated, AI and ML “deliver the momentum to change”. The life sciences has become a digital industry powered by AI and ML. For us at Novartis, it is not “if” or “when” AI and ML will help us in our commitment to reimagining medicine. Now, the focus is on scaling it across the entire organization to fuel our unbossed, inspired and curious culture.

I’d like to extend a word of thanks to my esteemed co-panelists, all of whom shared great insights that did wonders to demystify AI an ML and I look forward to continuing and broadening these conversations.

[1] NPR’s Tech Nation host Moira Gunn moderated the panel, which included Altruista Health CEO Aashish Kachru InveniAI LLC President and CEO Krishnan Nandabalan, GSK Consumer Healthcare Director of Search and Evaluation Michael Keane, AbbVie Head of AI in R&D Information Research and Senior Principal Data Scientist Brian Martin, Centrexion Cofounder and former CBO Kerrie Brady, and myself.

Is Virtual Reality the Future of Travel?

Bruno Villetelle travel blog

Travel entices nearly everyone. When we dream of walking crystalline beaches, wandering blissfully lost past nature’s most idyllic creations, or navigating the strange buzz of an exotic mega-city lit up at night, it’s difficult to be anything but enthralled. In fact, I’d bet that if most people could, they would take their friends, their loved ones, and travel together nonstop. But that dream comes with an unfortunate caveat: reality. The reality of most of our situations leaves us unable to travel; we’re too busy working, providing. Living. Such thoughts make for wonderful daydreams, but our real preoccupation is with life.

Virtual reality could change everything. If we can convincingly sink ourselves into virtual landscapes, experiencing in staggering depth and clarity the sights and sounds of faraway places, VR may one day be able to fool our senses into traversing the globe (and beyond), without leaving the convenience of home. As it stands, the technology is still raw; it has yet to trickle fully into the mainstream, and what we do have is only a fraction of what might be achieved with VR.

Nevertheless, wearable VR has improved substantially since the colossal market failure of reality augmentation device Google Glass only a few years prior. Personal VR headsets which offer levels of visual immersion bordering on realistic are now produced and sold by companies such as Oculus Rift, Sony, and Samsung, and efforts to create virtual travel experiences are already well underway.

State-sponsored tourism channels have been among the first to accept VR’s potential to show us what we wouldn’t otherwise see;  in November 2016, Thailand’s Tourism Authority released a series of 360-degree videos, which included depictions of an elephant sanctuary, as well as western Thailand’s Kung Lao cave. “We want consumers to be able to touch, feel, see, and hopefully one day smell Thailand,” comments Steven Johnson-Stevenson, Thailand’s tourism marketing authority for the eastern United States. Tourism Australia has also published a number of 360 degree videos, including clips of a Sydney sunset, and snorkeling among the Great Barrier reef’s vibrant wildlife.

Another one of VR’s valuable travel applications is its ability to allow prospective vacationers to sample locations, in order to decide on the ideal setting. Travel companies such as Delta Airlines and Lufthansa use Oculus Rift to give a taste of what their services offer; also, the Thomas Cook Group launched a “fly before you buy,” initiative, implementing VR to spirit browsing customers away on a helicopter journey above Manhattan, a trek straight up the Pyramids of Giza, and more. Marriott has taken VR vacation sampling a step beyond the rest; in 2015, the hotel chain rolled out its interactive “teleport stations,” which utilize Oculus tech to entice customers, displaying across all five senses the virtual details of Hawaii’s breathtaking obsidian beaches.

But we’ve seen VR do more than just simulate a destination; it can also introduce an intriguing layer to our travels themselves; for example, VR app Timelooper transports users back in time by simulating major historic events at particular locations. “When you visit a historical site, there’s an abundance of resources to understand facts and figures—when it was constructed, how it was made, how people lived there at the time—but the thing that’s missing is a way to emotionally and immersively connect connect with these places,” elaborates Andrew Feinberg, Timelooper’s Chief Operating Officer.

From simulating a compelling, virtual version of travel to augmenting the journey itself, there seems to be every reason to conclude that in coming decades VR will undoubtedly hold sway over where we go, how we get there, and what travel actually means.