Radhakrishnanand Pullapanthula | Pharmaceutical Analysis |

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Prof. Dr. Radhakrishnanand Pullapanthula | Pharmaceutical Analysis | Best Researcher Award

National Institute of Pharmaceutical Education and Research | India

Prof. Dr. Radhakrishnanand Pullapanthula is a highly accomplished pharmaceutical scientist and analytical research leader with over two decades of distinguished experience in both industry and academia. A quality-minded professional, he has built a reputation for excellence in analytical compliance, regulatory affairs, and strategic development in the pharmaceutical sector. With a career spanning more than 24 years, including over 12 years in senior management positions, Dr. Pullapanthula has contributed significantly to analytical research and development, project leadership, and regulatory compliance within the framework of international standards such as cGMP, FDA, and ICH. His expertise lies in analytical method development, impurity profiling, physico-chemical characterization, and life cycle management of complex pharmaceutical products, including ANDA and NDA applications.Dr. Radhakrishnanand has been a driving force in setting up GMP-compliant analytical laboratories and implementing best practices for quality and regulatory adherence. His technical mastery covers LC-MS/MS, GC-MS/MS, ICP-MS, LC-Q-TOF-MS/MS, HPLC, GC, and IC techniques, enabling him to develop and validate advanced analytical methods for drug substances, formulations, excipients, food, and herbal products. His pioneering work in impurity profiling, degradation chemistry, and reference standard qualification has had a lasting impact on analytical R&D and pharmaceutical quality systems. As a leader, he has successfully coordinated the establishment of ISO 17025:2005 and ISO 17025:2017 certified laboratories, and played a key role in achieving NABL accreditation and ISO certification for analytical facilities at Daicel Chiral Technologies–India and United States Pharmacopeia.In addition to his industrial achievements, Dr. Radhakrishnanand has held prominent academic and administrative roles, serving as Registrar (In-Charge) and a board-level member in key scientific and innovation committees. His contributions extend to serving as an Expert Member on several national panels including the DST-Technology Development Board, ANRF-Life Sciences, NGCMA, and the Pharmaceutical Policy Committee of Tripura. As a Board of Director at the Atal Innovation Mission, NIPER-Guwahati, he has actively promoted innovation and research excellence in the pharmaceutical sciences. He currently manages and coordinates major projects such as the “Quality Assessment and Value Addition Centre for Herbal Industry in the North-Eastern States of India,” funded by the Ministry of Commerce under the TIES scheme, with a project worth exceeding twenty crores.

Profile: Google Scholar

Featured Publications

Rao, D. V. S., Radhakrishnanand, P., Suryanarayana, M. V., & Himabindu, V. (n.d.). A stability-indicating LC method for candesartan cilexetil. Chromatographia.

Kumari Rayala, V. V. S. P., Kandula, J. S., & Radhakrishnanand, P. (n.d.). Advances and challenges in the pharmacokinetics and bioanalysis of chiral drugs. Chirality.

Rao, D. V. S., & Radhakrishnanand, P. (n.d.). Stress degradation studies on dutasteride and development of a stability-indicating HPLC assay method for bulk drug and pharmaceutical dosage form. Chromatographia.

Kaja, R. K., Surendranath, K. V., Radhakrishnanand, P., Satish, J., & others. (n.d.). A stability-indicating LC method for deferasirox in bulk drugs and pharmaceutical dosage forms. Chromatographia.

Vishnuvardhan, C., Radhakrishnanand, P., Navalgund, S. G., Atcha, K. R., & others. (n.d.). RP-HPLC method for the simultaneous estimation of eight cardiovascular drugs. Chromatographia.

Rao, D. V. S., Radhakrishnanand, P., & Himabindu, V. (n.d.). Stress degradation studies on tadalafil and development of a validated stability-indicating LC assay for bulk drug and pharmaceutical dosage form. Chromatographia.

Subba Rao, D. V., Surendranath, K. V., Radhakrishnanand, P., & others. (n.d.). A stability-indicating LC method for vardenafil HCl. Chromatographia.

Prof.Mehdi Khashei, Pharmaceutical Analysis,Editorial Board Member 1191

Published on by Top Pharmaceutical

Prof.Mehdi Khashei, Pharmaceutical Analysis,Editorial Board Member

Prof.Mehdi Khashei, at Isfahan University of Technology, Iran

Author Profile

 

  • Education📚:

    • Ph.D. in Industrial and Systems Engineering, Isfahan University of Technology (IUT), 2014
      • Thesis: Modeling Spaces Continuity Theory
    • M.Sc. in Industrial and Systems Engineering, Isfahan University of Technology (IUT), 2005
      • Thesis: Forecasting and Analysis of Isfahan Steel Company Productions Price in Tehran Metals Exchange using Artificial Neural Networks
    • B.Sc. in Applied Mathematics and Computer Science, University of Isfahan, 2001

  • Publications🏅:

    • Mehdi Khashei has authored numerous articles in reputable journals such as Energy Reports, Biomedical Signal Processing and Control, International Journal of Computational Intelligence Systems, and many others. His research primarily focuses on innovative methodologies like discrete deep learning-based intelligent classification, hybrid models for time series forecasting, and applications in medical decision-making and energy classification.

  • Research Focus🧪:

    • His research interests span across areas like intelligent systems, deep learning, chemometrics, medical informatics, and statistical modeling, contributing significantly to advancements in predictive analytics and decision support systems.

🎓Publication Top Noted:

Paper Title :An artificial neural network (p, d, q) model for timeseries forecasting

  • Authors   : JMehdi Khashei, Mehdi Bijari
  • Journal    : Expert Systems with applications
  • Year        : 2010
Paper Title :A novel hybridization of artificial neural networks and ARIMA models for time series forecasting
    • Authors : Mehdi Khashei, Mehdi Bijari
    • Journal   : Applied soft computing
    • Year : 2011
Paper Title :Improvement of auto-regressive integrated moving average models using fuzzy logic and artificial neural networks (ANNs)
    • Authors :Mehdi Khashei, Mehdi Bijari, Gholam Ali Raissi Ardali
    • Journal   :Neurocomputing
    • Year : 2009
Paper Title :A new hybrid artificial neural networks and fuzzy regression model for time series forecasting
    • Authors : Mehdi Khashei, Seyed Reza Hejazi, Mehdi Bijari
    • Journal   :Fuzzy sets and systems
    • Year : 2008
Paper Title :Hybrid structures in time series modeling and forecasting: A review
    • Authors : Zahra Hajirahimi, Mehdi Khashei
    • Journal   : Engineering Applications of Artificial Intelligence
    • Year : 2019