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Digital health M&A in pharma reaches new high in 2019 in bid for faster tech

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Digital health M&A in pharma reaches new high in 2019 in bid for faster tech

In an attempt to gain a foothold in the cash-laden tech industry, some biotechnology and pharmaceutical companies have begun snapping up choice digital health companies, with a few billion-dollar deals leading the trend.

Digital health deal values in biopharma jumped to $6.4 billion in 2019, largely thanks to software company Dassault Systemes Americas Corp.'s $5.9 billion acquisition of health tech company Medidata Solutions, according to an analysis by S&P Global Market Intelligence. Previous large-scale deals include Roche Holding AG's 2018 purchase of clinical intelligence data platform developer Flatiron Health Inc. for $1.9 billion and IBM Watson Health Inc.'s $2.6 billion deal for health analytics company Truven Holding Corp. in 2016.

The bulk of digital health M&A in the pharma and biotechnology sectors center around the premise that certain technological capabilities like artificial intelligence and machine learning can accelerate life sciences innovation, speeding along tasks such as drug discovery, clinical trials and data interpretation. Smaller startups have contributed to the M&A uptick, building on their own technological capabilities to further the digitization of drug development.

Flatiron's appeal to Roche, for example, was the company's ability to mine patient data for determining appropriate treatment. Since the acquisition, Roche has leveraged Flatiron's platform as a control arm in clinical trials, using the real-world data to compare against study findings, J.P. Morgan analyst Tycho Peterson reported in June 2019.

On the other end of the spectrum are companies like IBM Watson and Dassault Systemes — originally purely tech companies — which have used the biotech and pharma angle to break into the healthcare sector.

"We expect the attention from large corporates to increase over the next 10 years, including some notable acquisitions," Pitchbook analysts wrote in a 2018 report, referring to the entry of technology giants, including IBM and Google LLC's DeepMind.

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Digital health's many applications

Another motivator for pharma and biotech's pursuit of advanced tech is cutting costs. Taking a drug from the lab bench to market is a lengthy and expensive endeavor, costing upward of $19 million per clinical trial phase, according to the journal JAMA Internal Medicine. And in some fields, such as neuroscience, drug discovery is crucial, as scientists must determine the most viable drug candidate out of a group of seemingly promising molecular entities to take into costly clinical trials.

Exscientia Ltd., a digital health company that uses artificial intelligence for drug discovery, snapped up Kinetic Discovery Ltd. in 2018 to enhance identification of drug targets. Kinetic Discovery specializes in assessing molecular compounds and drug binding.

Multiple big pharmaceutical companies, including GlaxoSmithKline PLC, Roche and Celgene Corp., have sought out partnerships with Exscientia to speed up drug discovery with AI.

Some drugmakers have also turned to data-savvy startups for streamlining clinical trials. The startups are armed with greater technological capabilities to analyze the large data sets characteristic of years-long clinical trials.

Precision for Medicine Inc., which specializes in data informatics to identify biomarkers in research studies, snapped up SimplicityBio SA in 2019, adding machine learning and AI to its arsenal. A biomarker is a biologic characteristic that can be used as a marker for a condition.

Another startup, Datavant, Inc., purchased fellow open health data platform Health Data Link Inc. in June to aggregate and expand deidentified patient data, which can be used as real-world data in trials. Datavant partner PAREXEL International Corp. has done just that. Datavant is a subsidiary of Roivant Sciences Ltd.

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Other companies like Cypher Genomics Inc., acquired by Human Longevity Inc. in 2015, apply automation in data interpretation software used in the clinic.

Tech tools, like Mytrus Inc.'s and Clinical Force Ltd.'s applications and dashboards, can speed along administrative tasks in clinical trials, including disseminating informed consent and tracking trial sites.

Pitchbook said the drug industry's movement toward personalized and precision medicine is an area where digital health will prove useful. The gravitation toward more specific and tailored therapies, particularly in cancer treatment, has given rise to a greater focus on biomarkers and genomics, for example.

Besides Precision for Medicine, digitally inclined companies like SOPHiA GENETICS SA and Epinomics Inc. are eyeing genomics and biomarkers to drive personalized therapies. Helomics Holding Corp., bought by Predictive Oncology Inc. in 2018, is similarly focused on using artificial intelligence to profile patients' tumors and identify cancer treatments.

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Still, the often-hyped realm of digital health likely faces multiple challenges before achieving wide adoption in the strictly regulated pharma and biotech field.

The U.S. Food and Drug Administration, for one, has yet to work through the logistics of evaluating digital therapeutics, wearables and virtual trials. The regulatory agency has formed working groups to address these novel methods, but a standardized pathway for companies to seek approval for digital "medicines," like Pear Therapeutics Inc.'s opioid use disorder treatment, and submit virtual trial data has yet to emerge.

Large tech companies, including Apple Inc. and Inc., may churn out health-related innovations faster than pharma and biotech's rigorously tested therapies, but they will nevertheless need to contend with the regulatory process to gain the FDA's approval.

In the meantime, drugmakers and smaller digital health companies alike can mobilize their forces, whether that means striking new deals or poaching tech-savvy board members, to ensure their clinical data gets more efficient and advanced analysis.

"Artificial intelligence approaches are only as good as the data we can apply them to," Precision for Medicine CEO Matthew Hall said.