The USFDA defines real-world data (RWD) as ‘the data relating to patient health status and/or the healthcare delivery that is routinely collected from a variety of sources’, and real-world evidence (RWE) as ‘the clinical evidence regarding the usage and potential risks/benefits of a medical product obtained from analysis of RWD.’[1] RWD includes data from electronic […]
There has been a shift in the global healthcare ecosystem from volume-based to value-based payment model, thanks to a surge in data availability, interoperability, advancing health technologies, cost and competitive pressures, scientific advances, and increasing adoption of personalized medicine. The resulting availability of a large quantity of real-world data (RWD) has made it possible to […]
Real-world evidence (RWE) is derived from real-world data (RWD) sources, such as electronic health records (EHRs), claims data, data from product/disease registries, pharmacy data, social media, and pragmatic trials. RWE provides essential insights into the clinical experience, thereby complementing the information obtained from traditional randomized controlled trials (RCTs).(1) RWE has been extensively used for post-marketing […]
Drug makers usually put in rigorous efforts to fast-track and reduce the cost burden of regulatory decision-making by regulatory authorities like USFDA and EMA. As a part of these efforts, the interest in utilizing real-world evidence (RWE) for the approval process has considerably increased in the past few years.(1) Even though data from randomized controlled […]
Real-world evidence (RWE) has been used extensively for satisfying post-launch regulatory requirements, mainly about drug safety. Of late, it has been realized that RWE has a wide range of applications across various phases of a product lifecycle, starting from the pre- to post-launch phases. These applications aim to address the particular needs of different healthcare […]
Artificial Intelligence (AI) refers to a computerized system that performs physical tasks, cognitive functions, solves problems, and/ or makes decisions without overt human instructions.[1] First proposed by McCarthy in 1955, the concept of AI has been applied in many health-related areas, including clinical research, hospital care, drug development, disease diagnosis, prognosis, and treatment monitoring. Advancement […]
A patient registry has been defined as “an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition or exposure, and that serves a predetermined scientific, clinical or policy purpose.”(1) Patient registries provide an infrastructure for the standardized […]
Patients with serious, life-threatening health conditions and who have no available treatment alternatives, often want to know if and how they can receive early access to investigational products, sometimes even before they are approved by the regulatory agencies. “Expanded access programme” (EAP), also referred to as “compassionate use programme” or “managed access programme”, is a […]
Economic evaluations of health interventions focus on comparative analysis of alternative approaches concerning their costs and outcomes. These help healthcare decision-makers to take informed decisions about appropriate resource allocation for healthcare, such as the approval of new drugs, devices, or procedures. However, economic evaluations often face reporting challenges because of the enormous amount of information […]
