The Impact of A.I. on Life Sciences

In the coming decade, there will be few industries that aren’t impacted by the increasing sophistication and availability of artificial intelligence. AI is certain to influence companies across every sector by optimizing operations, automating processes, and disrupting current business models.

AI holds particular promise for the life sciences sector, where it has the potential to transform therapy development, glean valuable insights by analyzing huge data sets, and make precision medicine a reality for patients.

In this article, we cover a few of the key-ways artificial intelligence is set to have an impact on the life sciences sector in the near-term.

AI has a role to play in clinical trials

AI has an important role to play in clinical trials and therapy development. Drug development is a staggeringly expensive and time-consuming process, requiring up to fifteen years and $1 billion in investment to take an idea from concept to launch. What’s more, a significant portion of drug development trials ends in failure, meaning that vast amounts of investment go to waste.

The promise of AI in the context of clinical trials is its ability to bring more efficiency to the process. For example, AI can help with patient recruitment — a part of the trial process that can be particularly onerous. AI can also help to monitor drug adherence, and predict toxicity. Broadly speaking, AI has the power to optimize and streamline what is currently a very manual process.

AI facilitates smarter data mining

As healthcare and medicine have advanced, we have begun to collect more and more data on patients. Worldwide, researchers are amassing and sharing a wealth of data. Theoretically, this data should be an engine driving more sophisticated decision-making and clinical insights. However, in practice, the sheer breadth of such data makes it very difficult to analyze and mine for practical insights. AI can be used in service of solving this problem.

For example, AI can enable analysis of large sets of data in order to discover new indications for existing drugs. AI has previously been used to identify the use of magnesium as a possible treatment for migraine headaches, and there is hope that it will help to uncover insights into treatment of COVID-19 from the huge volumes of research currently being generated about the virus.

As healthcare providers now have more patient data than ever before in the form of genetic information and health records, AI is pushing the dream of more personalized therapies closer to reality. This is known as precision medicine and it entails developing drugs or treatments designed for small, specific populations rather than for patients en masse. By using AI to analyze data, the hope is that researchers can identify the treatments that are most effective for specific groups of patients.

The promise of AI for better patient diagnosis

Another area where AI has the potential to shine is in the diagnosis of patient illness and disease. In the future AI may be able to make more accurate diagnoses while simultaneously alleviating the burden on doctors to make such diagnoses, and in turn freeing up their time to spend on patient care.

In particular, there is promise to be found in using AI to interpret medical images such as x-rays. In this scenario machine learning algorithms are used to recognize similar images and, hopefully, identify disease from the earliest possible stage. Some research has already suggested that AI is at least as accurate as humans in making a correct diagnosis.

Though we can’t predict all the future impacts AI will have on the life sciences, it’s clear that this technology is the next wave of innovation in the sector. From bringing more efficiency to clinical trials to get drugs to market faster, to facilitating better patient diagnosis and unearthing insights from large swaths of data, AI has many promising and practical use cases in life sciences.

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