5 predictions for AI in 2019

By Melissa Fassbender

- Last updated on GMT

(Image: Getty/kishore kumar)
(Image: Getty/kishore kumar)

Related tags Artificial intelligence AI

While several companies touted the potential of AI to disrupt the drug development industry in 2018, what practical applications can the industry expect next year?

Artificial intelligence (AI) made waves in the pharmaceutical industry last year​, with several large-scale deals, partnerships, and announcements, as researchers predict a revolution ​in drug discovery and preclinical development.

In 2019, Lawrence Ganti, global president of life sciences for Innoplexus, which provides AI and blockchain-powered solutions for the pharmaceutical and financial services industries, has five predictions for AI:

1. AI will increase drug repurposing

When companies miss endpoints and hypothesis fail, Ganti noted that most move on to the next product – the drug “gets dumped”​ – even if it could have potential for a specific percent of the population.

“Pharma is one of the most wasteful industries,”​ he said. “But eventually, the pharma industry will see more drug repurposing and companies will do more with what they have because AI can identify the subset of the population for whom a drug will work for.”

Ganti added, “Whether it’s a failed or new drug, pharma companies will move toward approving drugs in specific disease areas with certain biomarkers.”

2. AI will optimize leads and find new targets

Similarly, to his first prediction, Ganti said AI will help researchers optimize leads and find new targets.

“In regards to optimizing new leads and finding better targets, the main differences lies in the fact that AI would not only help pharma companies repurpose drugs but also enable them to leverage all of their current assets,”​ he explained.

Ganti cited a current lack of biological understanding needed to “reposition a current asset and validate additional applications.” ​However, powered with AI, “pharma companies will have a better understanding of how they can leverage all of their current internal assets,”​ he said.

3. AI will increase enterprise efficiency

Some pharma companies are addressing the need to offload “lower cognitive tasks”​ by relying on robotic process automation, though Ganti called this a “fad”​ and “a low form of AI.”

“Real AI, however, can pull data that is not in the same file format, freeing up companies to focus on higher cognitive tasks,”​ he said. “This is important for large companies because data reflects the nature of their organization.”

The need to collate data is also driven by mergers and acquisitions, though data is often disparate even within one company. Ganti said, “AI can solve this by bringing all the data together.”

4. AI will enable computationally intensive drug design

With the help of AI, Ganti said more pharma companies will start the drug development process “from scratch,” ​building molecules for a subtarget before using computations and protein modeling to make predictions.

“Most companies upgrading with AI are in this particular market. And overall, this is fairly simply but it requires investment in computing power,”​ he said.

“The impact of this trend, however, means that pharma companies will create completely new drugs, optimize drugs to minimize side effects, and even take out structures in existing molecules that cause problems or aren’t as effective.”

5. AI will enable real-time, on-the-go results

The industry is collecting more data than ever before from wearables, smart devices, and home sensors​.

“The more things you can monitor about an individual’s health, then the more data you will have, and that data can then be analyzed for patterns and insights to make medicines more personalized,”​ said Ganti.

“However, with an increase in data, there will be an increased need to analyze data and do it fast. This is when pharma companies will need computing power, AI, and machine learning.”

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