ISO/TS TECHNICAL SPECIFICATION 16393 First edition 2019-02 Molecular biomarker analysis Determination of the performance characteristics of qualitative measurement methods and validation of methods Analyse de biomarqueurs moléculaires Deétermination des caractéristiques de performance des meéthodes de mesure qualitatives et validation des méthodes Reference number ISO/TS 16393:2019(E) osi @ IS0 2019 IS0/TS 16393:2019(E) COPYRIGHTPROTECTEDDOCUMENT @ IS0 2019 All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication may be reproduced or utilized otherwise in any form or by any means, electronic or mechanical, including photocopying, or posting on the internet or an intranet, without prior written permission. Permission can be requested from either IsO at the address below or Iso's member body in the country of the requester. ISO copyright office CP 401 : Ch. de Blandonnet 8 CH-1214 Vernier, Geneva Phone: +41 22 749 01 11 Fax: +41 22 749 09 47 Email: copyright@iso.org Website: www.iso.org Published in Switzerland ii @ IS0 2019 - All rights reserved IS0/TS 16393:2019(E) Contents Page Foreword ..iv Introduction .. 1 Scope. ..1 2 Normative references 3 Terms and definitions ..1 4 Characterization of a qualitative method via a validation experiment .3 4.1 Criteria for a standard measurement method .3 4.2 Performance of a validation experiment .3 4.3 Nature of test materials... .4 4.4 Requirements for replicate test samples. .4 4.5 Robustness (ruggedness) 5 4.6 Applicability 5 4.7 Selectivity ..6 4.8 Experimental design for a multi-laboratory study .6 4.8.1 Participating laboratories .6 4.8.2 Number of laboratories.. .6 4.8.3 Number of levels .6 4.8.4 Number of replicates per level and laboratory 7 4.9 Validation experiment under intermediate conditions 4.10 Expressing the results of a validation experiment. 7 4.10.1 General 4.10.2 Graphical representation of the data 10 4.11 Calculation of the confidence interval for the general mean, confidence interval andpredictioninterval .12 4.12 Calculation of prediction interval for PODs in each laboratory ..13 5 Statistical model for test result ..13 5.1 General .13 5.2 Basic model .13 5.3 Constraints in the model .13 5.4 General mean, m .14 5.5 Variance parameters ..14 5.6 Relationship of qualitative model to the quantitative model ..14 5.7 Derivationofalimitofdetection .15 Annex A (informative) Estimation of the mean and variance ..16 Annex B (informative) Hybrid modified Wilson interval model ..18 Annex C (informative) Maximum profile likelihood based on the probit model ..20 Annex D (informative) Maximum likelihood estimate based on beta binomial distribution ..22 Annex E (informative) Testing ofthe models via simulation ..24 Bibliography .27 @ IS0 2019 - All rights reserved ii