Published by BioTechniques

The widespread adoption of electronic health records has completely revolutionized the way health services store, process and disseminate patient data. Although a fairly primitive use of technology by today’s standards, this early effort of digitalization in the healthcare sector demonstrates the power of using healthtech to improve patient services. Things have come a long way since then; the added strain of the COVID-19 pandemic served to accelerate the adoption of new technologies that remove patient care bottlenecks and provide faster, deeper and more accurate insights into medical conditions. This article delves into the ways that digital solutions are transforming various facets of the healthcare industry – from drug discovery and development to the management of chronic illnesses – as well as detailing how these novel tools are changing the way clinicians and patients interact with medical data.

Set to skyrocket

Healthtech is defined as the application of digital technology to improve health or care delivery [1], and the industry is positively booming, with its current market size of over $220 billion expected to more than quadruple by 2032 [2]. The ever-growing number of tools employing AI, machine learning and other forms of data analytics holds the potential to improve efficiencies in almost every healthcare category – including wellness and disease prevention, screening and diagnosis, care delivery and finance operations – with technologies designed to streamline drug discovery and development predicted to exhibit the largest compound growth rate over the next decade [1].

The digitalization of drug discovery and development

The average return on investment within pharmaceutical R&D is at an all-time low [3] and, all too often, billions of euros are poured into the development of drugs that do not make it to market. To improve the success rate of the discovery and development process, many companies are turning to various digital tools to extract new insights from existing drug molecule libraries, genomic datasets, patient health records and medical imaging databases. This approach would be immensely time consuming – if not impossible – to achieve using traditional methods. As a result of recent developments, smart technologies are now being integrated into computational library screening processes to highlight drug-like molecules with specific properties, as well as being used to comb through electronic health records to identify biomarkers of disease progression that can feed into target discovery. Tapping into these data goldmines will help pharmaceutical companies speed up the development of new drugs, while increasing the chances of success. Recent research from financial services company Morgan Stanley suggests that even modest improvements in early stage drug development enabled by AI and machine learning could lead to an additional 50 novel therapies over a 10-year period, translating to more than $50 billion in opportunities [4].

Using real-world evidence to make real-world impact

AI and machine learning also have a role to play beyond drug discovery and development. These approaches are now being employed in clinical settings to analyze empirical, patient-specific data with the aim of improving patient-level outcomes, supporting clinical decisions and matching treatments to specific patient characteristics. This is especially important in traditionally under-served areas such as behavioral health; innovative scaleup Holmusk is using AI-powered analytics and digital solutions to improve clinical and research applications in this area. Founded in Singapore – and now also based in Basel, Switzerland – the company is using its NeuroBlu™ platform and proprietary natural language programming analytics to deliver high-quality, real-world evidence from over four million patients to pharmaceutical companies, researchers, payers, regulators and healthcare providers. Stefan Suter, Head of Holmusk Europe, explained: “Electronic health records provide a rich and extensive source of information that can enable better decision making for both physicians and drug developers. For example, Holmusk’s data helps pharmaceutical companies to plan and recruit for clinical trials more effectively, define patient subgroups, and exploit therapeutic gaps to develop more targeted treatments. Our datasets support the whole pharmaceutical value chain, from drug development and launch to the clinical use of a product. Enabling clients in the behavioral health space to make better decisions where the stakes are high is where Holmusk can make a real difference.”

A digital future

From refining diagnostics and improving patient care to optimizing clinical trials and streamlining drug development, it is clear that digital technologies are well on the way to transforming almost every aspect of the healthcare industry. Much of the innovation in this space is emerging from a new generation of startups originating from bustling healthtech hubs like the Basel area, which are hungry to use AI, machine learning and other novel analytical methods to solve real-world problems. These digital innovators are also making personalized care more accessible by providing patients with the tools they need to play a more active role in their wellbeing and, with the potential applications of healthtech seemingly limitless, healthcare could be on the brink of a true digital revolution.