Study Design
Anwendungsbegleitende Datenerhebungen (AbD)
Eine Anwendungsbegleitende Datenerhebung (AbD) ist eine nicht-randomisierte, vergleichende Evidenzgenerierung, die in der Regelversorgung durchgeführt wird. Der Gemeinsamen Bundesausschuss (G-BA) kann eine AbD anordnen, wenn die vorliegende Evidenz für ein Arzneimittel nicht zur Quantifizierung eines Zusatznutzens als ausreichend erachtet wird. Betroffen sind Arzneimittel für seltene Leiden (Orphan Drugs) sowie Arzneimittel mit speziellen Zulassungstypen (bedingte Marktzulassung oder Zulassung unter besonderen Umständen).
Pitfalls in the clinical trial submission process according to CTR
On January 31, 2022, the long-awaited Clinical Trials Information System (CTIS) portal for submissions under the Clinical Trial Regulation (EU) No. 536/2014 (CTR) went online. Since then, many of us have already gained first experiences with the portal – especially since all new clinical trials now have to be submitted via this portal and the deadline for the transition to CTR of ongoing clinical trials is clearly approaching.
Unveiling the Veiled Influences: Bias in Observational Studies and Its Profound Impacts on Medical Research
Observational studies serve as vital tools in uncovering insights into real-world healthcare scenarios. Yet, navigating the intricate landscape of scientific inquiry comes with its own set of challenges, and one of the most elusive adversaries is bias. In the catalogue of bias, developed by scientists of the University of Oxford, around 60 kinds of bias are described that might possibly influence clinical evidence ...
Patient Engagement in Drug Development: The Rise of Patient-centric Approaches
The concept of patient centricity has emerged over the last three decades. Although no clear definition of patient centricity exists and the scope for interpretation is wide, putting the patients‘ needs in the centre and systematically engaging patients in drug development activities and decision making could be seen as an essence of existing definitions.
Use of large language models in clinical research (part 2)
This is a follow-up on our previous blog entry on large language models (LLMs) and first experiences using the publicly available chatbots, based on LLMs. It is worth noting that during creation of this blog post, the AI technology already advanced and an upgraded version of model GPT- 3.5 (on which ChatGPT was based) has become available (GPT-4).
Use of large language models in clinical research (part 1)
The importance of artificial intelligence (AI) and its potential impact on the workforce has entered the limelight in the last weeks of the year 2022. News outlets and internet websites reported on a groundbreaking achievement in AI: the development of chatbots based on large language models (LLMs) that can be used by the general public in an intuitive, conversational and user-friendly manner