Volume : 13, Issue : 08, August – 2026

Title:

GLOBAL PHARMACOVIGILANCE REGULATIONS – HARMONIZATION OF FDA, EMA, MHRA AND CDSCO

Authors :

Kiran Gorana, Soma Sekhar Pulamarasetti*, Omkar Rai, Swetapadma Rout, Karan Gupta

 

Abstract :

Background: Pharmacovigilance has evolved from spontaneous adverse drug reaction reporting to a lifecycle safety science linking clinical development, post-marketing surveillance, risk minimization and regulatory decision-making. [18, 5, 6] This has been driven by the inability of pre-approval trials to detect rare, delayed, and population-specific harms [4, 3]. Objective: To critically evaluate the degree of harmonization of pharmacovigilance practices between the United States Food and Drug Administration (FDA), European Medicine Agency (EMA), Medicines and Healthcare products Regulatory Agency (MHRA) and Central Drugs Standard Control Organization (CDSCO) in terms of reporting standards, signal detection, risk management and digital modernization [18, 12, 17]. Data Sources: This review summarizes recent peer-reviewed literature and regulator-focused comparative studies on ICH pharmacovigilance guidelines, FDA post-marketing systems, EMA good pharmacovigilance practices, post-Brexit MHRA changes, CDSCO/PvPI development, and AI uses in pharmacovigilance, with preference for publications from 2018–2026 and landmark older contextual work as needed [2, 9, 8]. Review Methods: We conducted a narrative state-of-the-art synthesis as the focus of the topic is on regulatory structures, operational models and implementation differences, not pooled clinical effect estimates [18, 12, 5]. Main findings: The most harmonized areas are ICH-derived technical architecture such as E2B electronic reporting, common seriousness criteria, MedDRA coding, DSUR/PBRER structures and lifecycle pharmacovigilance planning [19, 12, 5]. There is divergence in expedited reporting clocks, governance models, risk minimization tools, signal detection workflows and legal accountability with further fragmentation post-Brexit and continuing capacity gaps in India [10, 15, 12, 8, 17]. The FDA is characterized by an active surveillance infrastructure, the EMA by highly codified GVP obligations, the MHRA by dual-system complexity following EU separation, and the CDSCO by rapid alignment but weaker active surveillance and underreporting constraints [5, 12, 8, 7]. Data quality, bias, transparency, privacy and validation issues [2, 9, 14] limit routine regulatory use. AI appears to improve signal detection, case processing and data integration. Conclusion: The current evidence favors a model of pragmatic harmonization, not full uniformity. The key policy challenge is to balance interoperable scientific standards with local regulatory flexibility, data governance and public health responsiveness [18].
Keywords: Pharmacovigilance; Adverse Reactions, Drug-Related; Postmarketing Product Surveillance; Risk Management; Regulatory Science; Artificial Intelligence

Cite This Article:

Please cite this article in press Soma Sekhar P et al., Global Pharmacovigilance Regulations – Harmonization of FDA, EMA, MHRA and CDSCO. Indo Am. J. P. Sci, 2026; 13(08).

REFERENCES:

1. Aarti, Singh, K. S., & Kumar, M. (2025). Role of Pharmacovigilance Programme of India (PvPI) in Adverse Drug Event Monitoring for medication safety in patient. International Journal For Multidisciplinary Research. https://doi.org/10.36948/ijfmr.2025.v07i01.36627
2. Algarvio, R., Conceição, J., Rodrigues, P., Ribeiro, I., & Ferreira-Da-Silva, R. (2025). Artificial intelligence in pharmacovigilance: a narrative review and practical experience with an expert-defined Bayesian network tool. International Journal of Clinical Pharmacy, 47, 932–944. https://doi.org/10.1007/s11096-025-01975-3
3. Amale, P. N., Deshpande, S., Yd, N., & Na, A. (2018). Pharmacovigilance Process in India: An overview. Journal of Pharmacovigilance, 6, 1–7. https://doi.org/10.4172/2329-6887.1000259
4. Basile, A., Yahi, A., & Tatonetti, N. P. (2019). Artificial Intelligence for Drug Toxicity and Safety. Trends in Pharmacological Sciences, 40, 624–635. https://doi.org/10.1016/j.tips.2019.07.005
5. Bernaus, C., & Bournissen, M. L. (2026). Global pharmacovigilance reporting: comparative analysis of adverse event obligations across five major regulatory authorities. Frontiers in Drug Safety and Regulation, 6. https://doi.org/10.3389/fdsfr.2026.1821686
6. De Abreu Ferreira, R. L., Zhong, S., Moureaud, C., Le, M. T., Rothstein, A. M., Li, X., Wang, L., & Patwardhan, M. (2024). A Pilot, Predictive Surveillance Model in Pharmacovigilance Using Machine Learning Approaches. Advances in Therapy, 41, 2435–2445. https://doi.org/10.1007/s12325-024-02870-5
7. Gupta, M., & Pant, H. (2026). Regulatory Requirement for Pharmacovigilance System in India: Gaps and Future Direction. International Scientific Journal of Engineering and Management. https://doi.org/10.55041/isjem07787
8. Ivr, J. G., & Srinivasan, R. (2025). Impact of Brexit on Pharmaceutical Regulations: EMA vs. MHRA. Reviews on Recent Clinical Trials. https://doi.org/10.2174/0115748871375964250531090843
9. Kompa, B., Hakim, J. B., Palepu, A., Kompa, K., Smith, M., Bain, P., Woloszynek, S., Painter, J. L., Bate, A., & Beam, A. (2022). Artificial Intelligence Based on Machine Learning in Pharmacovigilance: A Scoping Review. Drug Safety, 45, 477–491. https://doi.org/10.1007/s40264-022-01176-1
10. Lomeli-Silva, A., Contreras-Salinas, H., Barajas-Virgen, M. Y., Romero-López, M. S., & Rodríguez-Herrera, L. Y. (2024). Harmonization of individual case safety reports transmission requirements among PAHO reference authorities: a review of their current regulation. Therapeutic Advances in Drug Safety, 15. https://doi.org/10.1177/20420986241228119
11. Patel, R., Sachan, A. K., Chaohan, S., Tiwari, A., Giri, T., N., Ansari, A. S., Yadav, R. K., Siddiqui, E. M., Pandey, S. K., Yadav, B. S., & Chaudhary, N. (2021). Present era of drug safety in India: An overview. Journal of Pharmacovigilance and Drug Research. https://doi.org/10.53411/jpadr.2021.2.1.1
12. Reddy, N. S., Nagasree, K., Laxmi, P., & Kumar, S. (2026). An Analytical Study on Global Pharmacovigilance Regulations and their Role in Risk Management. International Journal of Current Trends in Pharmaceutical Research. https://doi.org/10.30904/j.ijctpr.2026.4999
13. Saini, A., Chandel, R., & Bala, A. (2026). Artificial Intelligence in Pharmacovigilance: Redefining Signal Management, Post-Marketing Drug Safety, and Adverse Drug Reaction Detection. International Journal of Research Publication and Reviews. https://doi.org/10.55248/gengpi.07.0626.17a16
14. Salas, M., Petracek, J., Yalamanchili, P., Aimer, O., Kasthuril, D., Dhingra, S., Junaid, T., & Bostic, T. (2022). The Use of Artificial Intelligence in Pharmacovigilance: A Systematic Review of the Literature. Pharmaceutical Medicine, 36, 295–306. https://doi.org/10.1007/s40290-022-00441-z
15. Singh, A., Twomey, K., & Baker, R. (2018). Global pharmacovigilance regulations: Call for re-harmonization. Clinical Trials (London, England), 15, 631–632. https://doi.org/10.1177/1740774518801592
16. Singh, P., Vaishnav, Y., & Verma, S. (2022). Development of Pharmacovigilance System in India and paradigm of pharmacovigilance research: an overview. Current Drug Safety. https://doi.org/10.2174/1574886317666220930145603
17. Tripathi, A., Kumar, A., & Das, D. (2026). Regulatory Harmonization in Indian Pharmacovigilance: Convergence with Global Standards and Unique National Adaptations. International Journal For Multidisciplinary Research. https://doi.org/10.36948/ijfmr.2026.v08i01.64639
18. Umaru, O., Adeyemi, A., Aderonmu, O., Bhangu, B. S., Dhaliwal, H. S., Lim, H., & Aremu, T. (2026). Global Pharmaceutical Regulation: Comparative Frameworks and Operations. Pharmacy, 14. https://doi.org/10.3390/pharmacy14020050
19. Wasiullah, P., Yadav, P., Vishwakarma, P., & Jaiswal, R. P. (2025). ICH Guideline for Pharmacovigilance: A Framework for Global Pharmacovigilance Practice. International Journal of Pharmaceutical Research and Applications. https://doi.org/10.35629/4494-100228082814

Volume : 13, Issue : 08, August – 2026

Title:

EVALUATION OF ANTIHYPERLIPIDEMIC ACTIVITY OF SAPINDUS EMARGINATUS IN RATS

Authors :

Chinthala Jamima*, Dr.R.narasimha Rao, Dr.N. Raghunandhan

Abstract :

Obesity and hyperlipidemia have become major disorders predominantly causing prevailing cardiovascular diseases and ultimately death. The prolonged use of anti-obesity drugs and statins for reducing obesity and blood lipid levels is leading toward adverse effects of kidneys and muscles, specifically rhabdomyolysis. The objective of this study is to evaluate potential of seeds of Sapindus emarginatus against hyperlipidemia. In this model of Hyperlipidemia, 30 adult male wistar rats (200-250gms) were evenly divided into 5 groups in both groups. Group-1 and Group-2 served as untreated and model controls respectively, while Group-3, 4 and 5 were the treatments groups which were simultaneously treated with standard, 100 and 200 mg/kg extract respectively along with High Fat Diet. On last day, blood samples for biochemical parameters, were obtained under inhaled diether anaesthesia. The outcomes of this study were expressed as mean standard error and data were evaluated by using analysis of variance followed by multiple comparisons. Oral administration of 100 mg/ kg and 200mg/kg body weight of Methanolic extract residual fraction of Moringa oleifera. Leaves exhibited a significant reduction (P < 0.01) in serum lipid parameters such as triglycerides, total cholesterol, low density lipoprotein (LDL), very LDL and increase in high density lipoprotein in hyperlipidemic rats when compared with hyperlipidemic control in both models. Our results demonstrated that Methanolic extract fraction of Sesbania grandiflora. Possessed significant antihyperlipidemic activity.
Keywords: Sesbania grandiflora, Cholesterol, LDL, triglycerides and antihyperlipidemic activity.

Cite This Article:

Please cite this article in press Chinthala Jamimaet al., Evaluation of Antihyperlipidemic activity of Sapindus Emarginatus in rats,, Indo Am. J. P. Sci, 2026; 13(08).

REFERENCES:

1. Amit G, Vandana S, Sidharth M. HYPERLIPIDEMIA: An Updated Review. Inter J of Biopharma & Toxicol Res 2011;1:81-89.
2. Virchow RP, Thrombose IG. In Gesammelte Abhandlungen zur Wissenschaftlichen Medicin. Frankfurt-am-Main, Meidinger Sohn & Company 1856, S 458-564.
3. Ankur rohilla, Nidhi Dagar, Seema Rohilla, Amarjeet Dahiya, Ashok Kushnoor. HYPERLIPIDEMIA- a deadly pathological condition. Inter J Curr Pharma Res 2012;4:15-18
4. Ross R, Glomset JA. The pathogenesis of atherosclerosis. N Engl J Med 1976;295:369-77.
5. Grundy SM, Vega GL. Hypertriglyceridemia: causes and relation to coronary heart disease – Semin. Thromb. Hemost 1988;14:249-64.
6. Dargel R. Lipoproteins and the etiopathogenesis of atherosclerosis. Zentralbl Allg Pathol 1989; 135: 501-504.