Händelser: Studentarbete, Arkitektur, Bygg- och miljöteknik, Data- och informationsteknik, Energi och miljö, Kemi- och bioteknik, Matematiska vetenskaper, Material- och tillverkningsteknik, Mikroteknologi och nanovetenskap, Produkt- och produktionsutveckling, Rymd- och geovetenskap, Signaler och system, Sjöfart och marin teknik, Teknikens ekonomi och organisation, Fysik, Tillämpad IT, Tillämpad mekanik, Rymd-, geo- och miljövetenskap, Arkitektur och samhällsbyggnadsteknik, Bioteknik, Elektroteknik, Industri och materialvetenskap, Informations- och kommunikationsteknik, Mekanik och maritima vetenskaperhttp://www.chalmers.se/sv/om-chalmers/kalendariumAktuella händelser på Chalmers tekniska högskolaWed, 03 Mar 2021 07:09:15 +0100http://www.chalmers.se/sv/om-chalmers/kalendariumhttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Examensarbete210305.aspxhttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Examensarbete210305.aspxPresentation av examensarbete<p>Online</p><p>​Avijit Singh: Design and analysis of pre-clinical experiments using a method combining multiple comparisons and modeling techniques for dose-response studies</p>​<br />Abstract: In the preclinical stage of pharmaceutical drug development, identifying and estimating the dose-response relationship between a compound and a clinical endpoint of interest is one of the most important and difficult goals. In the drug development process, two main goals of dose-response studies are (i) to establish that changes in dose lead to desirable (efficacy) or acceptable (safety) changes in the endpoint(s) of interest and (ii) to select a dose (or doses) that appears to be efficacious and safe. The aim of this thesis is to provide an overview of existing techniques and design the experiments which are appropriate for addressing both of these goals simultaneously. We have used a method combining multiple comparisons and modeling techniques (MCPMod) in designing the experiments and found out that we can reduce the required total sample size by using optimal design without affecting results negatively. We have analysed simulated data using MCPMod and observed that this method can be used to identify dose-response relationships and estimate doses at the required effect. We have compared two approaches of estimating doses and discovered that using a weighted average of all fitted models gives a similar result as compared to using the best fitted model. Finally we have investigated the possibility of detecting the presence of toxicity in response of few or many samples at higher doses and found that we can detect toxicity if there are many samples with toxic response at higher doses.