Market Insight on Artificial Intelligence

Artificial Intelligence in Healthcare M&A: On the Rise

David H. Crean, managing director for Objective Capital Partners, highlights the latest trends in mergers and acquisition (M&A) activities involving companies with artificial intelligence/machine learning platforms and technologies and their application to healthcare companies.

David H. Crean, managing director for Objective Capital Partners, highlights the latest trends in mergers and acquisition (M&A) activities involving companies with artificial intelligence/machine learning platforms and technologies and their application to healthcare companies.

Written by David H. Crean on 30.03.2020
Written by David H. Crean on 30.03.2020

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Artificial Intelligence

Advances in technologies, an incorporation of entrants from outside the industry and changing consumer expectations are driving a global shift in the healthcare landscape. Powerful forces such as chronic diseases and massive data collection continue to add pressure and are pushing traditional models of research and development, diagnostic and treatment paradigms and healthcare delivery. Companies in the sector must transform to be part of the conversation and relevant or risk being left behind. This transformation requires healthcare leaders to take numerous steps including adopting a consumer-centric focus, shifting to preventive and outcomes-based care models, engaging with nontraditional value chain partners, and driving improvements to access, quality, innovative and affordable care. In addition, these companies must embrace digital and technology enablers that offer artificial intelligence (AI) methods for data application.

AI is terminology that has been used synonymously with machine- and deep-learning. AI often can be described as software platforms comprising complex algorithms to analyze data, reach conclusions and anticipate problems with human-level expertise but without requiring direct human input. Machine-Learning involves continuous and repetitive processes by which machines are capable of integrating new data and improving performance over time without the need for explicitly programmed instructions. Deep Learning is a complex version of machine learning that involves multiple layers of abstract variables, for analysis at a scope and speed far beyond human capability.

AI appears to be infiltrating every industry and sector, such as allowing vehicles to navigate without drivers and mimicking the way humans speak. But for all the authentic and exciting ways it’s transforming the tasks computers can perform, there’s a lot of hype, too. Absence of a cohesive strategy to incorporate cloud platform and data pools, integrating and consolidating data warehouses, data hubs and databases as a single source of data, can easily send organizations into a tailspin. Heterogeneous data sources and diversity of data management technology add to the complexity and can further make it a management challenge. Advanced data quality and analytics governance on data practices are key success factors in its applications, today and tomorrow.

Converging Trends in Healthcare

Distinct trends are converging in healthcare, which means AI will come to define our new paradigm.

  • Value challenge- There is escalating demand from long-term, chronic disease, rising costs, often with an ageing population and limited resources. Yet we are continuing to invest in facilities and equipment that were built to solve a completely different set of needs such as acute healthcare needs rather than chronic and complex conditions that require treatment for the longer term.
  • Massive data- The amount of health data that is now available to us is beyond comprehension. Staying current with and being able to access this data is simply beyond the scope of any human individual, no matter how capable or intelligent.
  • Solutions- Information technology development in healthcare has been rapidly moving from products to services to solutions (Frost & Sullivan, 2016). The next decade is moving towards medical solutions to deliver intelligent solutions for both evidence and outcome-based health, focusing on collaborative, preventative care.
  • Managing one’s healthcare- Harnessing technology is providing consumers with the data and information they need to proactively manage their own health and wellness, and to make better, more informed decisions in partnership with their healthcare providers. The willingness of the general public to be more active participants in their own health and wellness has now reached critical mass.

In recent years, tech firms like Amazon, Google and Microsoft all have identified healthcare as focus areas and AI is one of the primary channels through which they are managing to make this entry.

Krishna Cheriath, BMS

Wide Variety of AI Applications in Healthcare

The possibilities for AI to run the gamut across healthcare is enormous. From improving the rates of drug discovery and clinical successes to reducing the costs associated with incorrect diagnoses and unnecessary treatments to helping patients avoid pricey procedures down the road through predictive monitoring. Life sciences and healthcare companies are moving into spaces and areas involving massive data, high R&D potential detailing the rapid rise in only the last few years involving AI-focused firms and technology. Although not covered in this writing, there is also a flurry of venture capital going into AI for drug development and digital health financings see continued momentum. There’s no shortage of enthusiasm and we are seeing an increase in deal flow associated with AI-based companies and technologies and their incorporation into healthcare companies and systems.

Transaction Deal Flow in Healthcare

While a number of life science companies have already entered the space through acquisitions, a large percentage of the bigger biopharma companies recognize that they need to do this. The Tufts Center for the Study of Drug Development (TCDD) and the Drug Information Association (DIA), in collaboration with eight pharmaceutical and biotech companies, conducted a survey during the fourth quarter of 2018, which found that 57% of small companies, 74% of mid-sized companies and 88% of large companies are using AI within their organizations. Most were using it for clinical patient selection and recruiting, as well as AI-enhanced literature review, while a smaller percentage were using it for genetic data analysis, target identification, and to generate small molecule leads. Of those not using AI, they cited a lack of skilled staff, regulatory concerns, budget constraints and a mistrust of unvalidated technologies. Although some small- and mid-sized biopharma companies are hanging back from investing in AI technologies, problems of rising costs, complicated diseases, stricter regulations and the pricing debate in Washington, could make partnering or mergers and acquisitions (M&A) a necessity.

Meanwhile, a number of AI companies have already signed deals with large life sciences companies, with some beginning to bear fruit. The successes are leading to more partnerships across the landscape. About 56% of respondents to the Tufts/DIA survey said their AI partnerships were focused on drug discovery/preclinical and 42% were focused on supply chain. Only 6% said AI had contributed to the regulatory approval of a drug at their organization. The hope, however, is that the technology will lead to better development decisions, safer and more cost-effective drugs, and streamlined business operations.

M&A and leveraged buy-out (LBO) activities over the past 30 months show an increasing appetite for deal completion. According to Cortellis deal database, there were 34 deals completed since 2017 (2019 YTD through August), with increasing deal flow demonstrated each year. Average deal sizes were $438.39m with a median deal size of $64.67m at a range of $70k to $1.9b. Non-control, corporate transactions over the same period involving strategic investments, licensing and partnering also show increasing transactional activities to get access to AI technologies. Twenty-four (24) deals have been completed with average deal sizes of $15.49m with median deal sizes of $10.01m with a range of $100k to $50m. Expect more deal flow to come as companies understand and harness AI better on the regulatory and evidence generation side. AI will be expected to drive actions and efficiencies to help with clinical evidence, speed to market and commercial decisions.

Final Thoughts

The convergence of AI and the healthcare sector was certainly inevitable and continues to change each day. The advent of machine-learning and deep-learning technologies capable of analyzing and synthesizing massive amounts of data with algorithms seems a natural fit for an industry in dire need of greater efficiencies. Successful organizations will likely be those that are willing to reach outside of their own space to transform. Many of these legacy-based companies have been doing things the same way for so long that it’s expected that change will be difficult. Companies that are unable or unwilling to move and participate could find it difficult to stay relevant, grow and transform their businesses.

Organizations in the healthcare sector will continue to lead the way aided by significant improvements and efficiencies from automation, digital, and AI platforms. In the future healthcare paradigm, there will be a greater focus on all areas of wellness/prevention and early detection. Some life sciences companies are already beginning to partner with medtech and other technology organizations around early screening. Rather than looking at an illness alone, life sciences companies will need to consider an entire disease state. They will need to identify potential partners who will help them improve prevention, early detection, precision diagnoses, and treatment. These companies will likely need to partner or merge with multiple players in this ecosystem to demonstrate, and commit to, value.

Disclosure

Objective Capital Partners is a leading investment banking advisory firm whose Principals have collectively engaged in more than 500 successful transactions serving the transaction needs of growth stage and mid-size companies. The executive team has a unique combination of investment banking, private equity, and business ownership experience that enables Objective Capital Partners to provide large enterprise caliber investment banking services to companies with annual revenues up to $500MM. Services include sale transactions, partnering/ licensing, equity and debt capital raises, valuation and comprehensive advisory services. The firm uses a proprietary process to work to achieve maximum company valuation, premium pricing, and high client satisfaction rates post-sale. The firm’s industry expertise is focused on 5 verticals including healthcare, life sciences, business services, technology, and consumer products. Additional information on Objective Capital Partners is available at www.objectivecp.com.

This article is provided for informational purposes only and does not constitute an offer, invitation or recommendation to buy, sell, subscribe for or issue any securities. Securities and investment banking services are offered through BA Securities, LLC Member FINRA, SIPC. Objective Capital Partners and BA Securities are separate and unaffiliated entities. While the information provided herein is believed to be accurate and reliable, Objective Capital Partners and BA Securities, LLC makes no representations or warranties, expressed or implied, as to the accuracy or completeness of such information. All information contained herein is preliminary, limited and subject to completion, correction or amendment. It should not be construed as investment, legal, or tax advice and may not be reproduced or distributed to any person.

Author

David H. Crean
David H. Crean

Ph.D, Managing Partner at Cardiff Advisory. Previously, Dr. Crean served as Managing Director for Objective Capital Partners

Dr. Crean has in excess of 25 years of transactional experience. Dr. Crean holds FINRA Series 79 and Series 63 licenses and is a FINRA Registered Investment Banking Representative through BA Securities, LLC.

In parallel to his investment banking and strategic advisory leadership for Cardiff Advisory, Dr. Crean currently serves as a Senior Advisor to Objective Capital’s Investment Banking services, and is in leading roles on the Boards of Directors for Histogen, Inc. (Nasdaq: HSTO) as Board Chairman and Chair of Audit, and the California Life Sciences Association (CLSA) as Chairman of Development and a member of the Executive Committee. He is a limited partner with a leading life sciences venture fund, Mesa Verde Venture Partners, and a member of Corporate Directors Forum. Dr. Crean is also a contributing author for Forbes.com through his work with Forbes Los Angeles Business Council and a contributing author for PharmaBoardRoom.com. For his outstanding advisory work, Dr. Crean was recognized by San Diego Business Journal for SD500 Most Influential Business Leaders in 2019 and 2020, M&A Advisors for the 2019 Investment Banker of the Year, San Diego Business Journal’s 2018 Healthcare Hero, 2017 Thought Leader of the Year and 2017 Advisor of the Year Awards. Dr. Crean is also active in the non-profit sector where he serves in leading Board of Director roles for the Association for Corporate Growth (ACG) San Diego as President, and as Chairman of the Board for the Alzheimer’s Association of San Diego/ Imperial Counties and Student Success Programs of the Charter School of San Diego.

Dr. Crean holds a Masters of Business Administration (MBA) Degree with a finance concentration from Pepperdine University Graziadio School of Management. Additionally, he holds a Doctorate of Philosophy (Ph.D.) Degree in Biophysics and a Masters of Science (MS) Degree in Oncology from the State University of New York at Buffalo. Dr. Crean also earned a Bachelor of Science (BS) Degree in Biology/ Pre-Med from Canisius College.

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