Top three healthcare trends in 2023 By The Business Research Company’s Healthcare and Lifesciences Director, Ravi Kiran.

1. Advent of Artificial intelligence (AI) and Machine Learning (ML) in healthcare

AI is being adopted very quickly in the medical field, with many medical devices such as imaging systems, smart robots, wearable technology and simulation platforms implementing AI capabilities, the medical devices industry is making its way ahead in the healthcare industry. The main medical specialties with AI-based medical innovations for medical devices include Radiology, Oncology and Cardiology.
AI helps automate the multiples processes including manufacturing, manages clinical trial databases and helps in drug discovery for the virtual screening of many compounds. The discovery process has historically been a funnel model with a large number of compounds being screened from HIT to Lead process, with attrition at every step—an inefficient process. AI has helped identify the most promising compounds and targets at every step of the research process to reduce the burden of screening large volumes of candidate molecules. Increasing data volumes drive the development of AI-based solutions. Big biopharma companies are integrating AI into their scientific process. The applications projected to drive most of the AI market in healthcare include drug discovery, precision medicine, medical imaging & diagnostics.

2. Introduction of Real-world evidence (RWE) or Real-world data (RWD)

Real-world evidence is the clinical evidence about the usage and potential benefits or risks of a medical product derived from analysis of RWD. RWD examples include information obtained via digital health technology, medical claims data, data from product or disease registries, and information derived from electronic health records.
Analytics and real-world data can speed up medication development and provide information that clinical trials are unable to. RWE can shed light on the effectiveness of treatments in particular patient subsets that may not have been seen in RCTs.
Real data has been used by pharmaceutical businesses to inform choices, respond to requests from external stakeholders, and strengthen the market position of their products. Recently, some companies have been able to profit from real-world evidence much more broadly thanks to increased regulator acceptance as well as demand from payers and physicians.

3. Personalized medicine and healthcare

There is a higher chance for patients to receive healthcare that is tailored just for them. A prime example of this is precision medicine. Medication and other therapy are specifically tailored to a group of patients based on characteristics like age, genetics, or risk factors, as opposed to employing a one-size-fits-all approach. The most advanced and precise forms of personalized healthcare take into account a person's genetic makeup or genome and can help doctors forecast how well certain drugs will work or if a patient is likely to have side effects. AI and ML technologies occasionally help with these forecasts.
Advancement in molecular diagnostics, genomics and sequencing technologies driving personalized medicine. A significant number of mutated genes have been identified in cancer and personalized therapeutics have been developed to treat cancer sub-types.
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