A list of six trends for 2020 in the age of digital and personalized health.
Augmented clinical trials bring many advantages to consume digital patient-centric information and optimize clinical development. Virtual, pragmatic, and hybrid trial designs will improve patient enrollment, compliance, and experience. They will also lead to improved trial outcomes as patient adherence, clinical biomarkers, and other areas of clinical benefit are more easily measured and analyzed during development. Additionally, decisions to protect patients against possible adverse events or risks of supply shortage can be addressed in real time. Artificial Intelligence (AI) and machine learning, supported by the Internet of Medical Things (IoMT), will serve as the analytics engine to enable this innovation in trial design by keeping patients and their data connected with researchers.
Pharmaceutical manufacturing is becoming increasingly digitalized and processes are changing to benefit from robotic process automation, digital twin simulation, and digital operator assistance (e.g., augmented reality approaches, use of image analytics).
In health care, social determinants of health are being applied to detect populations at risk of escalating health costs due to chronic diseases, demographics or behavioral patterns. An example is the use of income data or access to education; data points that can affect how people take care of their health. Secure data zones and data privacy guardians will need to be established to respect personal data privacy regulations (such as the EU’s GDPR) and to avoid unethical uses of data.
New primary care delivery models-“new digital front doors of health care”-are being established to help drive better patient outcomes, lower costs, and increase the ability of health care providers, payers, and governments to significantly impact health budgets. These models encompass extending primary care through virtual clinics, offering telemedicine services and virtual consults, and pharmacy chains establishing basic clinical care to facilitate patient access. These digitalized services, combined with analytics, machine learning, and AI, have the potential to transform the patient journey from the inside out.
We have just seen the start of a new revolution in medicine with in-vivo gene therapies combating the effects of mutations in somatic cells directly inside the body. These therapies (e.g., CAR-T, CRISPR-CAS9, RNAi, healthy gene delivery mechanisms) constitute a huge paradigm shift and bring a level of precision to the clinic not yet seen in clinical reality, although promised by researchers for a long time. However, the therapy (curing disease by changing faulty gene expression or translation, and their development and manufacturing processes) is very expensive. New cost models will need to be established for payers to decide on reimbursement and weigh the value against lifetime chronic disease states and the accompanying treatment regimens.
Artificial Intelligence is becoming available to everyone and can be used everywhere in health care and life sciences processes where information environments are kind to AI and dense, high quality, and integrated data are available (e.g., CT scans, EHR, clinical trial data, financial data). More attention will need to be given to semantically integrate data, as well as transparency and interoperability, for organizations to reap the benefits of these transformative technologies.
Mark Lambrecht, PhD, director of the SAS Global Health and Life Sciences Practice