Demonstration of Work
Projects, papers, and presentations.
Epigenetics and Therapeutics:
Mechanistic Insights, Associations to Health and Disease, and Future Considerations
MB 585: Industry Case Studies in Biotech
Spring 2024
Epigenetics, the study of heritable changes in gene expression that occur without alterations in DNA sequence, contains intricate relationships between epigenetic mechanisms, therapeutic interventions, and ethical considerations for emerging epigenetic therapy. By using the field as an understanding of dynamic regulation of gene expression, mechanisms involving DNA, RNA, and chromosome structure provide a foundation for unraveling the role of epigenetics in disease progression, offering promising diagnostic and therapeutic avenues for cancer and chronic diseases. Therapeutic challenges, such as off-target effects and unforeseen impacts to genetic regulation, underscore the need for continued refinement and innovation. Additionally, considerations regarding patient consent, equitable access to treatment, and the implications of epigenetic modifications on identity and privacy are crucial in shaping ethical frameworks for engaging epigenetic research with clinical practice. Epigenetics and future therapeutics is multifaceted, highlighting the pivotal role of epigenetic mechanisms and biomarkers in disease management while navigating the ethical complexities inherent in epigenetic interventions. Continued research and correlated communication are essential to address emerging therapeutic development challenges and ensure the responsible integration of epigenetic therapies into clinical practice.
Artificial Intelligence and Drug Development
MB 585: Industry Case Studies in Biotech
Fall 2023
Artificial Intelligence (AI) is the overarching ability for a computer to simulate human intelligence and learn from algorithms. This technology has infiltrated markets worldwide, with significant prevalence over the past five years. Specifically, AI is transforming the drug development landscape of the biotechnology sector. AI has the potential to revolutionize the industry by rapidly identifying novel drug candidates, predicting adverse effects, personalizing treatment regimens, and more. AI and its associated branches, such as machine learning (ML) algorithms, significantly reducing the time and costs associated with traditional drug discovery, offering a promising path toward more efficient and effective pharmaceutical solutions. While the promise of AI in drug development is undeniable, the technology is relatively new, necessitating a closer examination of bias, data privacy issues, and federal regulations. Ensuring the responsible and trustworthy use of AI is essential for its potential to benefit human health. In this review, prevalence and various applications of AI technology in drug development are analyzed, in addition to successful examples of AI's influence in the field, and necessary legal and safety considerations for this novel technology.