Faculty Bibliography

The integration of artificial intelligence (AI) in healthcare, known herein as Medical AI, has seen a remarkable increase in attention over the last few years. This study aims to provide a comprehensive analysis of the trends in venture funding in the medical AI sector in comparison to venture funding in healthcare and AI as a whole over the past decade, using data from the Pitchbook financial database, and its implications for the future of healthcare quality and delivery. An extensive review of venture investments in healthcare, AI, and medical AI (the overlap between healthcare and AI) sectors was conducted for a 10-year period from October 7, 2013 to October 6, 2023. The study used Pitchbook"™s database to catalogue deals across various stages, round numbers, and series, inclusive of all ownership models and geographic locations. The analysis focused on completed transactions, extracting descriptive statistics for deal flow, capital flow, and post-funding valuations while analyzing trends. The study found that the medical AI sector experienced a higher year-over-year growth in deal volume (P=0.01 compared to healthcare, P=0.08 compared to AI) and capital flow (P=0.01 compared to healthcare and P=0.03 compared to AI) over this time period, with all sectors witnessing a sharp stimulus during the coronavirus disease 2019 (COVID-19) stimulus period, alongside marked increases at the time of introduction of seminal AI technologies. This was followed by marked drawdowns with the onset of high inflation and high interest rates. Early-stage funding was dominant in medical AI, indicating a market leaning towards emerging technologies. Despite a decrease in total deal volume in recent years, there was a steady increase in median deal sizes and valuations, highlighting the sector"™s resilience and perceived value. The findings suggest that medical AI is a rapidly growing sector with significant investor interest, particularly in early-stage ventures. The findings align with the early stages of a valuation bubble, though the sector thus far has shown resilience and value growth despite broader economic fluctuations and reduced deal volume, indicating a selective yet robust investment environment.

Alopecia is traditionally classified into scarring and nonscarring subtypes, with etiopathologies ranging from androgen-mediated to immuno-inflammatory. Over 50% of men and almost 50% of women will experience some form of hair loss in their lifetime. Given this prevalence and the psychosocial significance of hair, understanding the pathophysiology and comorbidities of different types of hair loss is imperative. Other proinflammatory dermatologic disorders, such as psoriasis, are recognised to have systemic manifestations including an increased risk of cardiovascular (CV) disease, and are now considered CV risk-enhancing conditions. With increased recognition of the importance of systemic inflammation in promoting atherosclerosis, high prevalence, and improved treatment strategies, there is increased interest in establishing whether a similar association between alopecia and cardiovascular disease (CVD) exists. In this manuscript, we aim to review the current literature regarding CV risk in androgenic alopecia (AGA) and alopecia areata (AA). Additionally, we review the literature for cicatricial alopecias and highlight the need for more research into their potential associations with CV risk. Evidence from the identified AGA publications suggests an association of AGA with CV risk factors including hypertension, dyslipidemia, and insulin resistance, as well as with coronary artery disease. For AA, most of the identified studies found an association between AA and CV risk, though the relationships were not always statistically significant. Research on cicatricial alopecias and CV risk is limited and often contradictory. There is great need for more studies regarding the association between various types of alopecia and the development of CVD, and potential mechanisms. Particularly needed are more studies of cicatricial alopecias and potential associated CV risk. While some literature suggests that patients with alopecia have an increased risk of CVD, the lack of concrete evidence represents a notable gap in our current understanding.

IMPORTANCE/UNASSIGNED:Current measures of alopecia areata (AA) severity, such as the Severity of Alopecia Tool score, do not adequately capture overall disease impact. OBJECTIVE/UNASSIGNED:To explore factors associated with AA severity beyond scalp hair loss, and to support the development of the Alopecia Areata Severity and Morbidity Index (ASAMI). EVIDENCE REVIEW/UNASSIGNED:A total of 74 hair and scalp disorder specialists from multiple continents were invited to participate in an eDelphi project consisting of 3 survey rounds. The first 2 sessions took place via a text-based web application following the Delphi study design. The final round took place virtually among participants via video conferencing software on April 30, 2022. FINDINGS/UNASSIGNED:Of all invited experts, 64 completed the first survey round (global representation: Africa [4.7%], Asia [9.4%], Australia [14.1%], Europe [43.8%], North America [23.4%], and South America [4.7%]; health care setting: public [20.3%], private [28.1%], and both [51.6%]). A total of 58 specialists completed the second round, and 42 participated in the final video conference meeting. Overall, consensus was achieved in 96 of 107 questions. Several factors, independent of the Severity of Alopecia Tool score, were identified as potentially worsening AA severity outcomes. These factors included a disease duration of 12 months or more, 3 or more relapses, inadequate response to topical or systemic treatments, rapid disease progression, difficulty in cosmetically concealing hair loss, facial hair involvement (eyebrows, eyelashes, and/or beard), nail involvement, impaired quality of life, and a history of anxiety, depression, or suicidal ideation due to or exacerbated by AA. Consensus was reached that the Alopecia Areata Investigator Global Assessment scale adequately classified the severity of scalp hair loss. CONCLUSIONS AND RELEVANCE/UNASSIGNED:This eDelphi survey study, with consensus among global experts, identified various determinants of AA severity, encompassing not only scalp hair loss but also other outcomes. These findings are expected to facilitate the development of a multicomponent severity tool that endeavors to competently measure various disease impact. The findings are also anticipated to aid in identifying candidates for current and emerging systemic treatments. Future research must incorporate the perspectives of patients and the public to assign weight to the domains recognized in this project as associated with AA severity.