Dr. SREEKANTH THOTA

About

I currently serve as a Professor at the VAAGDEVI COLLEGE OF PHARMACY, Ramnagar, Hanamkonda, Warangal, Telangana, India. My academic journey began with a Bachelor's degree in Pharmacy from Kakatiya University, Warangal, India, followed by a Master's degree in Pharmacy from Rajiv Gandhi University of Health Sciences in Bangalore, India. Subsequently, I earned my PhD from Jawaharlal Nehru Technological University Hyderabad in 2011.
In recognition of my research endeavors, I was honored with the Research Promotion Scheme award sponsored by AICTE, New Delhi in 2012. Furthering my academic pursuits, I pursued postdoctoral research at Colorado State University in the USA during 2013. I was honored with the CAPES-Fiocruz Visiting Researcher award in 2013 and worked as a Visiting Research Scientist at CDTS-Fiocruz & LASSBio (UFRJ), Brazil from 2014 to 2018. My research focus is on Drug discovery, Drug design, and Medicinal chemistry with over 45 publications.

Employment

• VAAGDEVI COLLEGE OF PHARMACY PROFESSOR
  2025 - Present

Education

• Colorado State University Research Scholar
  2013 - 2013
• Jawaharlal Nehru Technological University Ph.D
  2007 - 2011
• Rajiv Gandhi University of Health Sciences M.PHARMACY
  2004 - 2006
• Kakatiya University B.PHARMACY
  1999 - 2003

Projects & Funding

Projects & funding information is unavailable.

Publications (62)

• From QbD to Explainable AI: Interpretable Random Forest Surrogates for Design Space Understanding of Voriconazole–β-Cyclodextrin Inclusion Complexes
  Journal of Pharmaceutical Innovation 2027 DOI: 10.1007/s12247-026-10957-5
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• From QbD to Explainable AI: Predictive Design Space Mapping of Lecithin/Chitosan Nanoparticles
  2026 DOI: 10.21203/rs.3.rs-9854829/v1
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• Ultrasound-responsive doxorubicin microbubbles engineered by QbD: enhanced in vitro anti-breast-cancer efficacy with attenuated cardiac cell toxicity.
  Research Square 2026 DOI: 10.21203/rs.3.rs-8565614/v1
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• PROTACs: Next-generation cancer therapeutics revolutionizing targeted treatment strategies
  In Silico Research in Biomedicine 2026 DOI: 10.1016/j.insi.2026.100386
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• From QbD to Explainable AI: Interpretable Random Forest Surrogates for Design Space Understanding of Voriconazole–β-Cyclodextrin Inclusion Complexes
  Research Square 2026 DOI: 10.21203/rs.3.rs-8665692/v1
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• Decision-Centric Explainable AI for QbD Optimization of Ultrasound-Triggered Drug- Loaded Microbubbles and Control Strategy Development
  Research Square 2026 DOI: 10.21203/rs.3.rs-8947026/v1
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• Explainable Machine Learning Using Taguchi-QbD Data for Digital Design Space Mapping of Pregabalin Extended-Release Tablets
  2026 DOI: 10.21203/rs.3.rs-9683753/v1
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• Machine Learning Modeling of D-Optimal Design Data for Metformin Hydrochloride Orally Disintegrating Tablets
  2026 DOI: 10.21203/rs.3.rs-9699705/v1
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• Explainable Machine Learning Using Taguchi-QbD Data for Digital Design Space Mapping of Pregabalin Extended-Release Tablets
  2026 DOI: 10.21203/rs.3.rs-9683753/v2
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• Design, Synthesis, and Pharmacological Evaluation of First‐in‐Class Multitarget N ‐Acylhydrazone Derivatives as Selective HDAC6/8 and PI3Kα Inhibitors
  ChemMedChem 2020 DOI: 10.1002/cmdc.201900716
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