The Future’s Not Near, It’s Here: How AI Can Transform Healthcare and How Female Founders Can Drive This Change
Written by Spring and Summer DigitalDx Ventures Fellow Sylvia Bouloutas
Advancements in Artificial Intelligence (AI) are revolutionizing medicine as we know it — and it’s only just the beginning. New AI applications are being used to efficiently diagnose disease, reduce diagnostic-related medical errors, develop new medications, and streamline the patient experience. In the coming years, AI-based systems in healthcare will only continue to augment physicians and help solve some of the most challenging healthcare problems. However, despite significant technological advancements in the healthcare industry, little progress has been made to bridge the gender gap for female healthcare founders and leaders. In order to advance forward, investors must look towards funding diverse founders.
The term “Artificial Intelligence” was first coined by John McCarthy for an academic conference held at Dartmouth in 1956. Since then, AI has made it possible for machines to learn and accomplish unique human like-tasks by processing large amounts of data and recognizing data patterns. AI is already impacting many industries and has the potential to significantly transform the way we live and work in the future. In the healthcare industry, AI will only continue to advance due to progress in computing power, leveraging algorithms, and the availability of large datasets. The size of the global artificial intelligence healthcare market is expected to reach $31.3 billion by 2025 and is growing at a compound annual growth rate (CAGR) of 41.5%.
The AI healthcare market is segmented by technology into two primary categories — machine learning and natural language processing. Machine learning is a statistical technique to find patterns in large data sets. In healthcare, machine learning has many applications and can be used for identifying disease and diagnostics, medical imaging, drug discovery and development, disease progression modeling, precision medicine and treatment and prevention of disease. Natural language processing helps computers read, interpret and understand human language. In healthcare, natural language processing can help turn complex clinical documentation, data and research (e.g., individual patient health records, genomic data, data from wearable health monitors, online reviews of physicians, medical imagery, etc.) into actionable knowledge.
Clinical Applications of Artificial Intelligence
Clinical applications of artificial intelligence are ubiquitous and encompass almost all aspects of modern healthcare. Numerous large technology companies, university research centers, hospitals and startups are working to build clinical applications of AI in healthcare, including early detection and diagnosis, treatment options, drug discovery, and genomics.
Early detection can guide physicians towards better-targeted therapies and can improve patient outcomes. Using AI’s ability to recognize patterns, AI applications can enhance the diagnostic process, and in many cases, can diagnose disease more accurately than physicians. One research study suggests that some deep learning algorithms achieved better diagnostic performance than a panel of 11 physicians. Last year, a team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Massachusetts General Hospital (MGH) created a new deep-learning model using 60,000 data points that can predict, from images obtained from a mammogram, if a patient is likely to develop breast cancer as much as five years in the future. Recent research suggests that Google’s deep-learning model was able to detect signs of lung cancer earlier and faster than a team of radiologists.
AI also has the potential to make drug discovery faster, cheaper and more effective by identifying patterns hidden in large volumes of data. Berg, a biotechnology company outside of Boston, has invested hundreds of millions of dollars to establish an R&D center that is using AI to identify potential treatments based on the precise biological causes of disease. Berg’s technology has developed compound BPM 31510, which is one of the first drugs in the world guided by AI to target and shrink cancer cells.
AI also has applications in genomics and gene editing. AI and machine learning techniques help researchers and physicians identify patterns within genetic data sets and build algorithms to make predictions about future diagnoses. As a result, patients can receive more personalized care solutions and physicians can make better decisions about future treatment and care. Google’s DeepVariant uses AI technology and deep-learning to turn high-throughput sequencing (HTS) into a more accurate blueprint of a full genome. Canadian company Deep Genomics is using AI solutions to decode the meaning of the genome and determine individual drug therapies based on the DNA, RNA and molecular machinery of the cell.
The Case for Female Founders
In many ways, healthcare is a female-dominated industry. Women are the primary healthcare decision-makers and caregivers in their households, comprise of 70% of the global healthcare workforce and are half of the healthcare consumer base. However, despite their influence in healthcare, women are under-represented in leadership positions across the industry. Only 4% of healthcare company CEOs are women and only one healthcare company in the Fortune 500 has a female CEO. Women are also severely underrepresented as VC (venture capital) investors and entrepreneurs. Only 12% of decision-makers in the venture capital industry are female and the majority of firms do not have a single female partner or GP. Low female representation in the VC industry is directly related to the funding gap for female founders, as female investors are twice as likely to invest in female-run ventures. As a result, female founders and entrepreneurs have learned to operate in an environment where 98% of venture capital funding goes to startups led by men. In the HealthTech space, research and data show that only 9.7% of investor funding goes to startups led by women and women make up of only 11% of partners in healthcare companies.
There are significant economic benefits to investing in diverse, female-founded startups. When women are able to secure initial funding for their startups, research suggests that firms with a female-founder performed 63% better than those with all-male founding teams. Furthermore, startups founded by women deliver twice as much per dollar invested than those founded by men. When female entrepreneurs raise a follow up funding round, female-founded companies are likely to exit quicker than male-only founding teams and have a higher internal rate of return (IRR) — 112% versus 48%. Finally, there is strong statistical evidence that diverse leadership and teams can boost overall company innovation. As this data suggests, women-led ventures, on average, are more capital efficient and have better ROI than male-only teams.
Looking Forward
From chronic diseases to cancer, there are endless opportunities to leverage AI technology to transform patient care. However, the same AI solutions that are so integral to the advancement of the healthcare industry are only as good as the team that builds them. A lack of female representation in healthcare is not only an obstacle for talented female founders who are solving important problems, but also will hinder the success of AI products to address the entire population and reflect the consumer-base. In turn, this will ultimately lead to biases in data and weaker patient solutions. In this new decade, the dialogue and action regarding female representation must progress equally as fast as the rapid pace of innovation in the healthcare industry. Investors must fund diverse founders today and help women set new records as leaders in healthcare. In fact, the success of the industry depends on it.
