Published in EPM Magazine: https://www.epmmagazine.com/op...
The advent of smart pharmaceuticals has substantially changed the way in which the pharmaceutical industry interacts with its patients. It is now possible to collect purer data faster, facilitating patients’ autonomy over their own health, and making the research and development (R&D) process more efficient for drug developers.
While some argue that greater patient autonomy may lead to increased data variability, the volume of data that can now be collected means that these anomalies can be quickly identified and addressed. Ultimately, purer data, collected at source and in greater quantities thanks to increased patient engagement, facilitates the advancement of pharmaceuticals whether traditional or ‘smart’ and therefore drives improved patient outcomes.
Digital empowerment
Patients empowered through digitalisation have provided pharma companies with the opportunity to collect significant quantities of real-world data previously unavailable to researchers. This is leading to increased insights across the R&D lifecycle as it is now possible to collect vast quantities of complete data, thus rapidly improving the drug development process. Digital data can be collected from the patient directly via wearable technology making its collection much more efficient and enabling clinical trials to be carried out remotely.
According to a 2016 study by Frost & Sullivan, a market research company, the US remote patient monitoring market is expected to reach a compound annual growth of 13.2% through 2020. Remote monitoring allows researchers to have access to data earlier in the drug development process, which in turn enables them to react more quickly to safety issues. This data can then be leveraged by the industry to develop medicines that optimise the benefit-risk profile for individual patients.
Providing patients with greater autonomy has also facilitated patient compliance with medicines. Self-monitoring has been proven to encourage drug adherence amongst patients, as shown by a 2017 study by Dr Lilla Náfrádi, researcher at the University of Lugano. Smart pills or Ingestible Event Markers (IEM), which have recently been approved by the FDA, help patients to feel empowered with regards to their own health, as well as informing R&D professionals with the data they need to reassess a treatment plan if necessary. The pill includes an embedded sensor that digitally tracks if patients have ingested it, offering a unique benefit for patient groups with typically low adherence. Thanks to their tracking capability, smart pills help patients adhere to their medicine while simultaneously alerting their care team of gaps in the regimen. The goal is to provide early intervention and support for those patients at risk of disease relapse through non-adherence.
With great power comes great responsibility
Although increased patient autonomy has resulted in the collection of vast quantities of data, it has also increased the potential for data inaccuracies, which, if not identified and addressed, could impact upon drug safety and efficacy. Data accuracy is critical for the advancement of smart pharma. One of the greatest challenges facing R&D teams throughout the pharmaceutical industry is having data that is consistent and reliable. The ability to manage and integrate data from source to drug utilisation is fundamental in the pharma advancements. As critical gaps in information cannot be corrected post processing, relevant and accurate information must be collected at source. Missing this opportunity means that access to valuable information may be missed for good.
Volumes of data create challenges of downstream processing and analytics. Responding to this the pharmacovigilance industry is beginning to apply artificial intelligence (AI), which makes it possible to sift, structure and collate data across internet sources, reducing manual effort through application of preloaded algorithms which can decipher human semantics. Clearly such algorithms have to be transparent and subject to human scrutiny to ensure they are operating appropriately and that the precision/recall of the AI engines is at a level that provides meaningful outputs.
Increased patient autonomy necessarily raises questions about patient confidentiality. Greater transparency and the sharing of patient data for further scientific research is an increasingly important issue for those conducting clinical trials, as well as for patients participating in the studies. A conflict remains between the appropriate sharing of clinical trial data for R&D, and the maintaining of patient confidentiality. The introduction of General Data Protection Regulation (GDPR) in 2018 is challenging some of the existing processes and in particular the secondary use of data, so the pharmaceutical industry must proceed with diligence and ensure consent to use patient information is obtained.
New technologies such as the blockchain — a decentralised data management system utilised for its security, transparency and traceability — are likely to become more commonplace in clinical trials. When applied to clinical trials, the blockchain can ensure authenticity and traceability of patient consent. The proof of consent can be timestamped and stored on the blockchain, notifying patients of any change in procedure requiring them to renew their consent for the sharing of their information. Most importantly, data can be encrypted via the blockchain, ensuring that a patient’s identifiable data cannot be revealed. Although still in the early stages of its development, the use of this technology in the pharmaceutical industry has the potential to have a significant impact on data security.1–3
Still in its infancy
Although the pharmaceutical industry has advanced patient autonomy over the last couple of decades, smart pharmaceuticals are still very much in their infancy. New technologies such as the blockchain will allow for transparency in the sharing of information while maintaining the highest levels of privacy. As increasing numbers of patients collect their own data, it is likely that the manufacturers of these technologies, such as wearable devices will move from supplying the industry, to sharing aggregated data directly with the patients.
While very attractive in the post-approval setting, how patient feedback is managed during drug development will have to be considered carefully to avoid bias and changing outcomes. As the trend for patient autonomy progresses, patients will become increasingly well informed and the collection of efficient, accurate and secure data, and its application to R&D, will become increasingly important.
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