FDA de­vel­op­ing guid­ance on re­al-world da­ta qual­i­ty is­sues, of­fi­cials say

As the FDA grap­ples with how to use re­al-world da­ta for reg­u­la­to­ry de­ci­sions, two FDA of­fi­cials wrote in a per­spec­tive pub­lished last Fri­day in the Clin­i­cal Jour­nal of the Amer­i­can So­ci­ety of Nephrol­o­gy that the agency is de­vel­op­ing guid­ance on da­ta qual­i­ty is­sues unique to the re­al-world da­ta set­ting and re­lat­ed study de­sign con­sid­er­a­tions.

Al­iza Thomp­son and Mary Ross South­worth of the Di­vi­sion of Car­dio­vas­cu­lar and Re­nal Prod­ucts with­in FDA’s Cen­ter for Drug Eval­u­a­tion and Re­search (CDER) ex­plain: “Al­though the FDA has ex­pe­ri­ence us­ing ob­ser­va­tion­al (non­in­ter­ven­tion­al) study de­signs in the post­mar­ket set­ting to eval­u­ate prod­uct risks in broad pop­u­la­tions, us­ing non­ran­dom­ized method­olo­gies to de­ter­mine ef­fec­tive­ness can be prob­lem­at­ic be­cause of con­cerns about the abil­i­ty to ad­e­quate­ly con­trol for con­found­ing, se­lec­tion bias, and the pos­si­bil­i­ty of mis­clas­si­fi­ca­tion er­ror.”

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