In the Iranian pharmaceutical industry, distributors widely rely on trade credit as the primary demand-management instrument to preserve market share. However, unplanned and excessive extensions of credit periods have become a major source of pharmacy liquidity crises, sharp reductions in order volumes, occasional bankruptcies, and, ultimately, diminished patient access to essential medicines. This study develops an optimal trade-credit coordination model and demonstrates that scientifically calibrating the credit duration, using this prevalent industry practice, can substantially alleviate financial distress. The model is formulated within a Stackelberg leader–follower framework and incorporates temperature-dependent Weibull deterioration to capture the cold-chain constraints of pharmaceutical products. Concave fractional programming is employed to establish that the annual total profit function is strictly pseudo-concave, thereby guaranteeing the existence and uniqueness of a global optimal solution for feasible contract parameters. The solution methodology combines an efficient iterative search algorithm with exhaustive brute-force validation implemented in Python. The proposed approach requires no additional financial resources or regulatory changes and can be readily implemented using existing industry practices. Numerical results indicate profit improvements of up to 19.7% and more than a threefold increase in order quantity relative to the decentralized baseline. Overall, the framework provides distributors and pharmacies (retailers) with a practical, cost-free means of transforming a common demand-management instrument into an effective coordination mechanism that enhances profitability, cash-flow stability, and patient access to medicines.