In　the　field　of　intelligent　digital　healthcare,　Continuous-flow　microfluidic　biochip　(CFMB)　has　become　a　research　direction　of　widespread　concern.　CFMB　integrates　a　large　number　of　microvalves　and　large-scale　microchannel　networks　into　a　single　chip,　enabling　efficient　execution　of　various　biochemical　protocols.　However,　as　the　scale　of　the　chip　increases,　the　routing　task　for　CFMB　becomes　increasingly　complex,　and　traditional　manual　routing　is　no　longer　sufficient　to　meet　the　requirements.　Therefore,　this　paper　proposes　an　automatic　routing　framework　for　CFMB　based　on　Genetic　algorithm　(GA)　and　A*　algorithms.　Specifically,　we　adopt　a　two-stage　A*　algorithm　to　design　the　routing　between　modules,　using　the　routing　results　obtained　from　the　A*　algorithm　as　the　basis　for　evaluating　the　quality　of　solutions　in　the　GA　algorithm.　Then,　the　GA　algorithm　is　used　to　search　for　the　optimal　approximate　solution　in　the　solution　space.　Experimental　results　show　that　this　method　can　reduce　routing　length　and　minimize　routing　crossings,　thereby　improving　the　parallel　transmission　speed　of　reagents　on　CFMB.　This　approach　provides　a　feasible　solution　for　large-scale　automated　routing　of　CFMB　in　the　field　of　intelligent　digital　healthcare.　©　The　Author(s),　under　exclusive　license　to　Springer　Nature　Singapore　Pte　Ltd　2024.