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Faculty Profile

Kiran Khanna

Assistant Professor

Qualification

Pharm. D

Contact Info

[email protected]

Bio

Bio

Kiran Khanna, Pharm D, has over Two years of experience as a clinical pharmacy practitioner and one and a half years pharmacy practice educator. Throughout his career, he has expertly performed numerous chemotherapy dose calculations and overseen the preparation of more than 1,500 chemotherapy dilutions. He is highly skilled in subjects such as Pharmacotherapeutics, Social Preventive Pharmacy, Clinical Research, Community Pharmacy, and Clinical Pharmacy Practice.

He has extensive experience includes managing clerkship programs and leading antibiotic stewardship initiatives, particularly for Pharm D students. He has provided hands-on training in Therapeutic Drug Monitoring (TDM) and Analytical Toxicology using HPLC and HPTLC machines. Additionally, he has guided five undergraduate and three postgraduate students in research projects focused on method development and validation for narrow therapeutic index drugs used in TDM.

He expertise also extends to dose calculations, TPN dilutions, and he has completed certificate courses in Health Research Fundamentals and Research Writing. He has been actively involved in offering free GPAT coaching to pharmacy students at SRIHER and holds a BLS certification. Currently, he is pursuing a PhD specializing in Therapeutic Drug Monitoring using LC-MS.

Educations

Research Interest

Projects

A Short Term Cross Sectional Retrospective Study on Assessing Procalcitonin As a Biomarker For The Various Infectious Disease

This study aims to evaluate procalcitonin (PCT) as a biomarker for diagnosing bacterial infections in various infectious diseases. Procalcitonin has shown potential in distinguishing bacterial from viral infections, particularly in conditions like pneumonia, sepsis, and urinary tract infections. The study will be a retrospective, cross-sectional analysis of patient records from a hospital, focusing on those diagnosed with bacterial infections and tested for PCT levels. We will assess the sensitivity, specificity, and predictive value of PCT in comparison to other diagnostic methods such as cultures, imaging, and clinical signs.

The primary goal is to determine whether procalcitonin can accurately guide the diagnosis and management of bacterial infections, potentially reducing unnecessary antibiotic use. Data will be collected from patients aged 18 or older, including clinical details, PCT levels, and microbiological results. Statistical analysis will include evaluating the diagnostic performance of PCT using ROC curve analysis and comparing it to other biomarkers like C-reactive protein (CRP).

By evaluating the clinical utility of PCT, this study aims to enhance infection management, improve antibiotic stewardship, and contribute to better patient outcomes in infectious disease care.

Method Development And Validation Of Methotrexate and Vancomycin For Therapeutic Drug Monitoring in HPLC Technique.

The objective of this project is to develop and validate reliable HPLC-based methods for the quantification of Methotrexate (MTX) and Vancomycin (VCM) in biological matrices, specifically for use in Therapeutic Drug Monitoring (TDM). Methotrexate is a chemotherapeutic agent used in cancer treatment and autoimmune diseases, while Vancomycin is an antibiotic commonly used to treat serious infections caused by Gram-positive bacteria, including MRSA. Both drugs have a narrow therapeutic index (NTI), meaning small variations in drug levels can lead to serious toxicities or ineffective treatment. Therefore, precise and accurate measurement of these drugs is crucial for adjusting dosages to achieve therapeutic efficacy while minimizing adverse effects.

The study will focus on developing a sensitive, reproducible, and selective HPLC method that can accurately measure plasma or serum concentrations of MTX and VCM in patients undergoing treatment. The method will be optimized for key parameters, including sample preparation, chromatographic conditions (e.g., mobile phase composition, column selection, flow rate), and detection methods (e.g., UV, fluorescence detection).

Method Validation will follow regulatory guidelines, assessing parameters such as accuracy, precision, specificity, linearity, limit of detection (LOD), limit of quantification (LOQ), and recovery. The validated method will be applied to monitor drug levels in clinical samples, aiding in personalized dosing regimens and improving patient outcomes.

This project aims to establish a robust HPLC method for TDM, ensuring safe and effective use of Methotrexate and Vancomycin in clinical practice.

A Review On Preterm Birth in AI Driven Analysis a Future Perspective

Preterm birth, defined as delivery before 37 weeks of gestation, remains a significant global health issue, contributing to high rates of neonatal morbidity and mortality. Despite advances in prenatal care, the early identification and management of women at risk for preterm birth remains a clinical challenge. In recent years, Artificial Intelligence (AI) has emerged as a promising tool to enhance early prediction, diagnosis, and prevention of preterm birth by analyzing vast amounts of clinical, genomic, and imaging data that would be difficult for traditional methods to process.

This review will provide a comprehensive overview of current AI-driven approaches in the field of preterm birth, highlighting the integration of machine learning (ML), deep learning (DL), and data mining techniques for predicting preterm delivery risk. The focus will be on the use of AI in analyzing electronic health records (EHRs), maternal biomarkers, ultrasound images, and lifestyle factors to develop predictive models with high sensitivity and specificity.

We will explore the future potential of AI in personalized medicine for preterm birth prevention, including AI’s role in identifying high-risk pregnancies earlier, optimizing interventions, and improving patient outcomes. Challenges in AI implementation, such as data quality, model interpretability, and ethical considerations, will also be discussed.

The review will offer insights into the promising future of AI-driven analysis in obstetrics, with the potential to revolutionize preterm birth management and reduce its global burden.

Assessing Metabolic Syndrome in Non alcoholic Fatty Liver Disease In Treatment Approach

Non-Alcoholic Fatty Liver Disease (NAFLD) is a condition characterized by excessive fat accumulation in the liver in individuals who consume little to no alcohol. NAFLD is closely associated with metabolic syndrome, a cluster of conditions including obesity, insulin resistance, hypertension, dyslipidemia, and elevated blood glucose levels. As the global prevalence of NAFLD rises, understanding the relationship between metabolic syndrome and NAFLD has become crucial for developing effective treatment strategies and improving patient outcomes.

This project aims to assess the impact of metabolic syndrome on the pathogenesis, progression, and treatment of NAFLD. The primary focus will be on identifying the key metabolic factors that exacerbate liver damage in NAFLD patients, including insulin resistance, dyslipidemia, and central obesity, and how these factors interact to increase the risk of liver fibrosis, cirrhosis, and hepatocellular carcinoma.

The project will also explore treatment approaches for NAFLD, with a specific emphasis on how managing metabolic syndrome can improve liver health. This includes evaluating pharmacological interventions (e.g., insulin sensitizers, lipid-lowering agents) and lifestyle modifications (such as dietary changes, weight loss, and exercise) in the context of both NAFLD and metabolic syndrome. We will examine evidence from clinical trials, epidemiological studies, and current guidelines to develop a holistic approach to treating these coexisting conditions.

By assessing the link between metabolic syndrome and NAFLD, this project will provide valuable insights into more effective, individualized treatment strategies that address both the liver disease and the underlying metabolic abnormalities, ultimately improving patient outcomes and reducing the burden of NAFLD globally.

Awards & Recognitions

Best paper Presentation in international conference in VISTAS

Best E-Poster presentation in Justifying LC-MS in Therapeutic Drug Monitoring

News

Membership

Member in International Society for Pharmacoeconomics and Outcomes Research Europe

Admissions

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