Traditionally, studies have been run with a process of study design, study conduct, study report. Whilst this is more straight-forward it is not flexible and does not allow for modifications or changes that may be desirable during the course of a trial. An adaptive design allows for the flexibility of interim reviews of the data, followed by pre-specified changes to the trial based on the review whilst maintaining the integrity of the trial, interim reviews may also result in outcomes such as a sample size re-estimation These prior planned adaptations are different to ad hoc protocol amendments, as the adaptations are already allowed for in the protocol.
The volume of digital data in healthcare is projected to increase more rapidly in the coming years than any other sector. On a day-to-day basis it is vital that clinical teams ensure they are maximising the value, not only of their own trial data but also of the wealth of external data for example electronic healthcare records, real-world data and peer-reviewed research published in journals.
The ability to utilise this data requires not only an understanding of what is available but how to access the data, work with the structure of the data, understand the quality and inherent biases and importantly apply the right methodology to extract value. In addition to the large volume of standard data generated on a clinical trial there can be a raft of other, more specialised data, such as genomics, proteomics, wearables and comprehensive measurements all of which rely on the skills of an experienced data management, programming and statistics team to utilise.
Showcasing the varied technical abilities of programmers, statisticians and data scientists within PHASTAR, the company has had a number of papers chosen for presentation at the PhUSE EU Connect conference in Amsterdam (10-13th November 2019). A total of 8 oral presentations and 2 posters will cover topics from a diverse set of areas that include: Analytical Risk-based Monitoring, Application Development, Coding Tips & Tricks, Data Standards and Governance, Real-world Evidence, Scripts & Macros and Standards Implementation.
There has been a growing emergence in the utilisation of basket studies and it’s not difficult to see why. Progress in genomics, tumour biology and statistics has led to advances in “precision oncology”. Cancers that were once viewed as homogeneous in terms of location and treatment strategy are now better understood to be increasingly heterogeneous across biomarkers and genetically determined subgroups. No two cancers are the same; tumours differ from patient to patient and few patients may noticeably improve with treatment, whilst others experience no benefit at all. As a result, we have seen a shift towards targeted agents, and it has become more common for trials to focus on a specific mutation at a particular location.
When thinking about the timeframe from initial drug discovery to regulatory review, we need to embrace novel clinical trial designs that improve efficiency. With this in mind, there has been an observable trend towards investigating multiple target-treatment pairs in parallel, either within, or across tumour types. The term “master protocol” refers to a general framework whereby multiple parallel drug studies are operated under one overarching protocol. A basket trial is a type of master protocol that tests the effect of one drug on a single mutation in a variety of tumour types. That is, they include patients with a certain genetic mutation in common regardless of the site or origin of cancer in the body, so patients have cancer at a variety of sites such as lung, breast, prostate, etc.
The theme of the 25th Society for Clinical Data Management (SCDM) annual conference in Baltimore was to raise awareness of the upcoming trends in the industry and reflect on how they will affect the clinical data management community.
The leadership forum convened a day ahead of the conference. It was an excellent opportunity for industry experts to come together, present their views and discuss how emerging study designs, regulations, and technology innovations are reshaping the role and profile of clinical data management. The core of our discussions was the first of 3 whitepapers from the SCDM released in June 2019, “The Evolution of Clinical Data Management to Clinical Data Science.”
