The pharmaceutical industry needs design tools to identify greener and more resource-efficient process routes. Current model-based solvent selection methodologies often focus on the choice of solvent in a single unit operation, with fixed operating conditions. In particular, the two key stages of synthesis and separation are usually treated independently. This often results in the use of different solvents for each processing task, which typically requires energy-intensive solvent swap operations. In the current paper, we present a novel computer-aided approach based on computer-aided mixture/blend design (CAMbD) that couples property prediction with simple process models and optimisation to simultaneously identify optimal solvents and anti-solvents, compositions and process conditions for integrated synthesis and crystallisation. Solvents are chosen using key performance indicators (KPIs) that quantify mass efficiency and product quality. The proposed methodology is illustrated by identifying promising reaction and crystallisation solvents for the synthesis of mefenamic acid from 2,3-dimethylaniline and 2-chlorobenzoic acid. Furthermore, multi-objective optimisation is deployed to highlight the trade-offs between the solvent or process E-factor and safety indicators, and between the solvent E-factor and crystal yield. The inclusion of mass-based KPIs and safety specifications ensures that only high-performance solvents are chosen. The findings of our approach are expected to guide the rational selection of solvents for greener pharmaceutical manufacturing during early-stage process development.