Routing　and　application　mapping　are　critical　stages　in　the　design　of　continuous-flow　microfluidic　biochips　(CFMBs).　The　routing　stage　determines　the　channel　network　connecting　components　and　ports,　while　application　mapping　schedules　fluid　transportation　and　wash　operations　based　on　the　designed　biochip　architecture.　Existing　methods　typically　handle　these　stages　separately:　routing　focuses　solely　on　physical　metrics　without　considering　subsequent　scheduling　requirements,　while　application　mapping　adopts　one-shot　scheduling　strategies　that　can　lead　to　suboptimal　solutions.　This　paper　proposes　an　integrated　path-driven　methodology　that　jointly　optimizes　routing　and　application　mapping.　For　routing,　we　develop　a　hybrid　particle　swarm　optimization　algorithm　that　incorporates　conflict　awareness　and　channel　utilization　strategies.　For　application　mapping,　we　introduce　an　iterative　approach　that　leverages　historical　scheduling　information　to　progressively　optimize　fluidic-handling　and　wash　operations.　Experimental　results　on　both　real　and　synthetic　benchmarks　demonstrate　significant　improvements　over　state-of-the-art　methods,　achieving　reductions　of　22.05%　in　total　channel　length,　21.79%　in　intersections,　21.97%　in　total　delay　time,　and　8.30%　in　biochemical　reaction　completion　time.　The　proposed　methodology　provides　an　effective　solution　for　the　automated　design　of　CFMBs　with　enhanced　physical　and　operational　efficiency.