Rodolpho C. Braga

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Education

Federal University of Goiás
Goiânia, Brazil

2015, Ph.D. in Medicinal Chemistry

I developed a profound understanding of the challenges and potential applications of AI in drug discovery and metabolomics. I was particularly fascinated by the significant role that NMR spectroscopy plays in elucidating the structure and dynamics of biomolecules. With the advent of AI techniques, I realized the immense potential in leveraging these technologies to enhance the analysis and interpretation of NMR data in the context of drug discovery and metabolism

Federal University of Goiás
Goiânia, Brazil

2011, MSc. in Pharmacy

I had the chance to explore how machine learning algorithms are used in drug discovery and metabolism. I gained a thorough understanding of the difficulties encountered in this field, including the extensive analysis of chemical and biological data, the identification of potential drug candidates, and the prediction of their toxicity profiles and metabolic pathways

Federal University of Santa Maria
Santa Maria, Brazil

2004, BSc. in Chemistry

Organic and Computational Chemistry

I have always found the intersection of technology and pharmaceutical research and development to be fascinating as a passionate scientist. I successfully concluded my academic journey by obtaining a doctorate degree in medicinal chemistry. Over the past decade, this achievement has provided me with valuable industry experience. Through my professional experience, I have gained a profound understanding of the challenges that the sector encounters. I am fully dedicated to devoting my life to the development of innovative solutions for these pressing problems.

Throughout my diverse career, I have gained valuable experience and expertise in various positions, which has continuously enhanced my knowledge in the field. I had the notable role of being a senior toxicologist and drug discovery specialist, where I utilized AI systems for complex projects. I played a significant role in the development of the In Silico Toxicology Platform iS-Tox® between 2017 and 2018. In 2017, I had the opportunity to contribute my expertise to the Drugs for Neglected Diseases Initiative (DNDi). During this time, I served as a computational chemistry scientist on the Lead Optimization Latin America project (LOLA).

Despite having achieved these accomplishments, I am constantly seeking new opportunities within the industry. During my time as a visiting professor of medicinal chemistry at the University of Turin (UniTO) in 2015 and 2016, I had the honor of mentoring the upcoming generation of scientists. I was honored to receive recognition for my contributions to predictive modeling, analytics, and data science through the American Chemical Society's (ACS) CINF Scholarship for Scientific Excellence in both 2012 and 2014. However, I felt a strong urge to fully embrace my passion.

As a result, I established InsilicAll, a pioneering drug discovery platform based in Latin America. Our platform utilizes AI and computation to accelerate the development of small molecule and protein therapeutics. Additionally, we prioritize the evaluation of toxicological safety during the design process. During my tenure as the leader of InsilicAll, we have achieved significant advancements in the field of drug discovery, resulting in the successful completion of numerous projects. The platform's unique approach to therapeutic development has received recognition from reputable entities like Apex-Brasil, Biominas Brasil, and ABIQUIFI. InsilicAll was recognized as a "hidden champion" among healthcare startups.

By assisting innovative startups, the Brazilian healthcare industry has the potential to promote collaboration and growth, ultimately benefiting patients and society. As the founder and CTO of InsilicAll, I am dedicated to promoting innovation in the pharmaceutical industry. With my expertise in predictive modeling, analytics, and data science, I see InsilicAll as a notable biotech player poised to make significant advances in drug discovery and toxicology.