Society for birth defects research and prevention's multidisciplinary research needs workshop 2022: A call to action.
Madhumita BasuKembra L HowdeshellSonja A RasmussenKristal A RychlikThomas B KnudsenDana L ShueyWilliam SlikkerPublished in: Birth defects research (2023)
The Society for Birth Defects Research and Prevention (BDRP) strives to understand and protect against potential hazards to developing embryos, fetuses, children, and adults by bringing together scientific knowledge from diverse fields. The theme of 62nd Annual Meeting of BDRP, "From Bench to Bedside and Back Again", represented the cutting-edge research areas of high relevance to public health and significance in the fields of birth defects research and surveillance. The multidisciplinary Research Needs Workshop (RNW) convened at the Annual Meeting continues to identify pressing knowledge gaps and encourage interdisciplinary research initiatives. The multidisciplinary RNW was first introduced at the 2018 annual meeting to provide an opportunity for annual meeting attendees to participate in breakout discussions on emerging topics in birth defects research and to foster collaboration between basic researchers, clinicians, epidemiologists, drug developers, industry partners, funding agencies, and regulators to discuss state-of-the-art methods and innovative projects. Initially, a list of workshop topics was compiled by the RNW planning committee and circulated among the members of BDRP to obtain the most popular topics for the Workshop discussions. Based on the pre-meeting survey results, the top three discussion topics selected were, A) Inclusion of pregnant and lactating women in clinical trials. When, why, and how? B) Building multidisciplinary teams across disciplines: What cross-training is needed? And C) Challenges in applications of Artificial Intelligence (AI) and machine learning for risk factor analysis in birth defects research. This report summarizes the key highlights of the RNW workshop and specific topic discussions.
Keyphrases
- artificial intelligence
- gestational age
- machine learning
- public health
- quality improvement
- big data
- clinical trial
- pregnancy outcomes
- healthcare
- deep learning
- randomized controlled trial
- pregnant women
- type diabetes
- advance care planning
- adipose tissue
- transcription factor
- heat stress
- hiv testing
- cross sectional
- climate change
- polycystic ovary syndrome
- insulin resistance
- metabolic syndrome
- human immunodeficiency virus