Anna Matranga, PhD, MBA, CA-AM, AMC Alliances & Consulting, explores the vital considerations and potential pitfalls when implementing new technologies in clinical trials. This is part of our series on clinical data collection and management.
There are many articles in the press on the current and future benefits of data collection using digital and mobile technology in clinical trials and beyond. They describe how technology will enable the provision of real world data (via direct access to patients) to facilitate the reimbursement of drugs with a “proven therapeutic value”, to promote faster drug development and to lower drug development costs for the pharma industry. These technologies will “engage” patients via the usage of apps on their personal mobile phone providing relevant information on studies, therapies and diseases as well as enabling data collection for the clinical and/or post-marketing surveillance studies (“internal & open source data”). These articles demonstrate the potential for easier access to patient data (on health signs, mobility, day-to-day activities as well as safety & efficacy data from CTs) in the drug development process.
As part of this technology wave (or deluge), there is an important need to develop (and acquire from other industries) the competencies in data science, informatics, business intelligence and alternative statistical approaches to manage this technology. The new business model for drug development necessitates the management of the mountains of data being collected. Over recent years the entry of new CIOs into the pharma industry has been visible and is key in providing the strategy for the acquisition and development of this “big data” competency to “evolutionise” the pharma business model.
In addition, it is important in the engagement and retention of patients in the treatment development process to remind ourselves that we don’t gain the interest of patients and investigators by having the best technology or wearable devices (albeit a short-term thrill), but rather by having the best treatments for their health problems. And part of that treatment is the time invested to follow-up with patients on their condition, their progress and their well-being. This is an integral part of (health) care provided by investigators or physicians and facilitated by mobile technologies that not only enable clinical data collection, but also provide personal patient updates, a follow-up medical appointment with transport options, and a forum in which patients can raise their particular questions, share them with other patients and receive guidance.
A Clear Vision
When considering what data to collect and manage, it is key to remember that technology developed in-house or provided by external partners or providers (the recommended approach as it’s a fast-moving market and enables quicker, cheaper access to technology) should support company objectives across the entire business organisation rather than vice versa. Jumping on the bandwagon of integration of new technology without a clear vision of where we are heading and what the technology will provide in terms of benefits to the business and to patient communities will only cause major problems. These can include poor design of development programmes, undue expenditure and potential delays to business growth. We may use the language of being “data driven”, but we are primarily “patient-focussed”, “science -focussed” with the aim of bringing value to patients and the healthcare community through the development of medical therapies and solutions.
Thus the data collection technologies connecting investigators/physicians, patients, labs, imaging centres and other expert centres need to enable a “continuum of care” in a real world data environment to gain a better insight of what’s going to provide real therapeutic value.
The Challenges to be Faced
Some of the challenges being addressed as we move forwards are:
- Due diligence and selection of technology: The chosen data collection technologies must support the business strategy and enable the investigator site and patient engagement. Plus, the availability (internally and/or externally) of data analytics capabilities to demonstrate therapeutic value, personalised medicines and reimbursement potential.
- Implementation and integration: Is this R&D only or company-wide? What is the compatibility of these technologies with internal IT platform architecture and systems?
- Implementation management: There must be availability of adequate scientific and IT resources with relevant experience and competencies, plus flexibility in the management of fast changing technologies. This requires internal adaptation to new collection methods and the continuity of long-term data collection in clinical/post-marketing/observational studies.
Explore other posts from our clinical data series here.