Medical Device trials are sometimes considered less intricate than drug development studies, however medical device studies have complexities that span across regulatory challenges, product types and unique statistical analyses and study designs.
AdvaMed, an association of medical device makers, released a report saying that the medical device industry has the potential to reach $30 billion USD in the next ten years “if proper regulatory framework is provided to the sector”.
This being said, challenges are present for both device developers and consumers. Consumers are after an affordable product that is available as early as possible, while device makers are anxiously seeking funding in the initial stages and then looking to streamline the trial process to get a product to market quickly and within budget. In the middle are the regulatory authorities who throw up roadblocks when it comes to patient safety and device efficacy.
As of 2014, the EMA is requiring more sophisticated clinical trials by eliminating the equivalence principal as an acceptable market-ready justification and proposing more post-market follow up. These reforms mirror the process already in place by the FDA, however the FDA has recently reached a decision on data systems and will not regulate devices that merely “display, store or transfer information”. The decision is the FDA’s attempt to not meddle in software and IT and promote more innovation in the sector.
Therefore, how important is a clinical data strategy in this growing sector?
Medical device companies need to think about strategy from conception to market – from preparing due diligence ready datasets for funders to post-market safety surveillance for regulatory authorities.
The medical device market is growing because of market entry from new startups looking to introduce new, innovative products to the market. However, these startups often need to secure funding for further development. Preparing your datasets in a due diligence manner is an important first step and companies should consider the following options:
How to outsource your study data:
- Centralizing Study Data through a specialized company: centralizing data in the early stages of device development promises common assessment methods, uniform traceability of data and the centralization of study metrics.
- Functional Service Provision: relying on a specialized clinical data company to provide a scalable team of resources at hourly or daily rates for a determined period of time.
Preparing your study data:
Implementing CDISC standards helps both traceability and cross analysis of datasets. There must be clear traceability from analysis results, to analysis datasets and to SDTM datasets. The FDA announced in 2014 that it is establishing guidelines on the use of CDISC for electronic submissions of study data in applications and it is most likely that guidelines requiring CDISC standard conformity is in the near future.
Technologies such as ePRO and EDC can help keep costs under control, especially if there are low-cost options Implementing an EDC solution into your medical device trial can provide immediate feedback, more accessible trial information, and higher data quality. It can facilitate an adaptive approach, or in the case of a trial that is showing a negative trend, it can allow for early termination, thereby reducing the risk to patients and reducing the cost of a trial.
Implementing a cloud-based solution improves the quality of data through automated edit and discrepancy checks, faster data cleaning, audit trails and compliance with GCP and regulatory guidelines.
The FDA has made a recent effort to improve communication with medical device makers. Preparing datasets and reports for regulatory submission are crucial steps for medical device companies, and they should have expert consultants to help. Involving an expert biostatistician from the beginning can help with the protocol development and study design.
Since statisticians involved in medical device trials must balance potentially expensive products, long follow-up periods, possibly large sample sizes, and unique endpoints, sophisticated trial design can help account for these changes. The FDA accepts the use of Bayesian design in medical device trials since it combines data from previous studies and the ongoing study to make changes to the study if necessary.
Consultant statisticians can also facilitate the communication between the device makers and regulatory authorities by interpreting and explaining clinical trial design and results.
CROS NT has extensive experience, both in the U.S. and Europe, in the area of medical device study design and analysis for regulatory submissions. We have worked with multiple startups and late stage device companies including work on novel, Class III devices and consulting on de novo Class II devices. If you need trial design and statistical assistance on an upcoming study, inquire about an initial consultation with one of CROS NT’s principal biostatistician.