Advancing pediatric medical device development via non-dilutive NIH SBIR/STTR grant funding

A novel maturity index for assessing medical device startups

Background

Startup companies in the healthcare sector often fail because they lack sufficient entrepreneurial, regulatory, and business development expertise. Maturity models provide useful frameworks to assess the state of business elements more systematically than heuristic assessments. However, previous models were developed primarily to characterize the business state of larger nonmedical companies. A maturity index designed specifically for startup companies in the medical product sector could help to identify areas in which targeted interventions could assist business development.

Methods

A novel MedTech Startup Maturity Index (SMI) was developed by a collaborative team of academic and industry experts and refined through feedback from external stakeholders. Pediatric medical device startups associated with the West Coast Consortium for Technology & Innovation in Pediatrics (CTIP) were scored and ranked according to the SMI following semi-structured interviews. The CTIP executive team independently ranked the maturity of each company based on their extensive experiences with the same companies.

Results

SMI scores for 16 companies ranged from 1.2 to 3.8 out of 4. These scores were well aligned with heuristic CTIP rankings for 14 out of 16 companies, reflected by strong correlations between the two datasets (Spearman's rho = 0.721, P = 0.002, and Kendall's tau-b = 0.526, P = 0.006).

Conclusions

The SMI yields maturity scores that correlate well with expert rankings but can be assessed without prior company knowledge and can identify specific areas of concern more systematically. Further research is required to generalize and validate the SMI as a pre-/post-evaluation tool.

Turning Neural Prosthetics Into Viable Products

Academic researchers concentrate on the scientific and technological feasibility of novel treatments. Investors and commercial partners, however, understand that success depends even more on strategies for regulatory approval, reimbursement, marketing, intellectual property protection and risk management. These considerations are critical for technologically complex and highly invasive treatments that entail substantial costs and risks in small and heterogeneous patient populations. Most implanted neural prosthetic devices for novel applications will be in FDA Device Class III, for which guidance documents have been issued recently. Less invasive devices may be eligible for the recently simplified “de novo” submission routes. We discuss typical timelines and strategies for integrating the regulatory path with approval for reimbursement, securing intellectual property and funding the enterprise, particularly as they might apply to implantable brain-computer interfaces for sensorimotor disabilities that do not yet have a track record of approved products.

Quantification of US Food and Drug Administration Premarket Approval Statements for High-Risk Medical Devices With Pediatric Age Indications

IMPORTANCE

Medical device companies submit premarket approval (PMA) statements to the US Food and Drug Administration (FDA) for approval of the highest-risk class of devices. Devices indicated for the pediatric population that use the PMA pathway have not been well characterized or analyzed.

OBJECTIVE

To identify and characterize high-risk devices with pediatric age indications derived from PMA statements.

DESIGN, SETTING, AND PARTICIPANTS

In this cross-sectional study of PMA statements, those statements containing the words indicated or intended for medical devices listed in the FDA PMA database as of February 2020 were retrieved. Age indications were manually annotated in these approval statements via PubAnnotation. Based on the PMA identification from the PMA statements, device metadata including product codes, regulation numbers, advisory panels, and approval dates were queried.

MAIN OUTCOMES AND MEASURES

The main outcome was discernment of the distribution of devices indicated for the pediatric population (neonate, infant, child, and adolescent). Secondary measures included outlining the clinical specialties, device types, and lag time between the initial approval date and the first date of an approval statement with a pediatric indication for generic device categories.

RESULTS

A total of 297 documents for 149 unique devices were analyzed. Based on the manual age annotations, 102 devices with a pediatric indication, 10 with a neonate age indication, 32 with an infant age indication, 60 with a child age indication, and 94 with an adolescent age indication were identified. For indications for patients from age 17 to 18 years, the number of devices available nearly doubled from 42 devices to 81 devices. Although more than half of the surveyed devices had a pediatric age indication, many were available only for a limited range of the pediatric population (age 18-21 years). For indications for patients from age 0 to 17 years, the mean (SD) number of clinical specialties at each age was 7.27 (1.4), and 12 clinical specialties were represented from ages 18 to 21 years.

CONCLUSIONS AND RELEVANCE

In this cross-sectional study on device PMA statements, a gap was identified in both quantity and diversity of high-risk devices indicated for the pediatric population. Because the current scarcity of pediatric devices may limit therapeutic possibilities for children, this study represents a step toward quantifying this scarcity and identifying clinical specialties with the greatest need for pediatric device innovation and may help inform future device development efforts.