This study examines the dynamic relationship between Gross Domestic Product (GDP) and pharmaceutical exports in India, utilizing time-series data from 1995-2022. The analysis employs econometric techniques to explore both short-term and long-term relationships between the variables. For stationarity, Phillips-Perron (PP) test is employed, which confirms that both GDP and pharmaceutical exports are integrated of order one, I (1). The Johansen Cointegration Test indicates no long-run equilibrium relationship between the variables. Consequently, a Vector Autoregression (VAR) model is applied to analyze short-term dynamics, with the optimal lag length determined using the Akaike Information Criterion (AIC). The Granger Causality Test reveals no causal relationships between GDP and pharmaceutical exports in either direction, suggesting that changes in one variable do not significantly influence the other in the short term. These findings highlight the need for further exploration of factors driving the pharmaceutical sector's contribution to economic growth, including research and development, foreign direct investment, and government policies. The study provides insights for policymakers and stakeholders to better harness the potential of the pharmaceutical industry in fostering sustainable economic development.