A Case study of Pharmaceutical programming in Preparing CRFs to Tables, Listings and Graphs analysing data of a Single-centre, Randomized, Single-Dose, Open-label, 4-way Cross over study. <\/p>\n\n\n\n
A leading international\npharmaceutical company involved in manufacturing of drugs. <\/p>\n\n\n\n
\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nA\npharmaceutical company approached Guires to develop integrated SAP (that\nincludes a detailed description of all patient population, and statistical\nanalyses to be carried out on the data collected during the clinical\ninvestigation), for the integrated summary of safety (ISS) and integrated\nsummary of Efficacy (ISE), based on the research objective and requirement\nanalyses. The requirements were to produce Tables, Listing and Graphs (TLGs)\nfor Phase IIa based on pre-defined objectives and hypothesis (i.e., in this case, bioavailability and dose proportionality\nendpoints). Besides, the client also requested Guires to validate the TLG\nthrough an independent review of\nprogramming code by a statistical programmer, different from the one who generate\noriginal programs. Finally, to produce a clinical statistical report (CSR) in\nconjunction with the preparation of a full clinical report\n\n\n\n<\/p>\n\n\n\n
The study was Phase 1, open-label, randomised, single-dose<\/strong>,\ncross-over study to estimate the dose proportionality and\nbioavailability in TD delivery system relative to comparator immediate-release\ntablet formulation in adult healthy volunteers. The study statistician worked\nclosely with the client to get an in-depth insight on clinical trial and the\nstudy, trial planning, the way it has been conducted and reported, and about\nregulatory requirements involved with it. The statistician also worked with\nin-house medical experts to refine the objectives and identified variables that\nwere required from the client\u2019s end. This includeds type of design and\ncomparison, randomization and blinding method, definition and measurement of\nprimary and secondary indicators, test hypothesis, definition of analysis set,\nplan for efficacy and safety evaluation and statistical analysis, principles\nfor the analysis of primary indicators and expected method of analysis, and\nfinally generalized principles and methods for explanator trials. The datasheet\nwas shared to us that contained participant information including their\ndemographic, clinical parameters including their body mass index, medical\nhistory, physical examination, electrocardiogram (ECG), routine laboratory\ntests (blood chemistry, haematology, and urinalysis. Prior to database lock, we\ncross-checked for any mismatches with the data shared and the objectives\n\/endpoints. <\/p>\n\n\n\n The draft of statistical analysis plan\n(SAP) and TLF and other necessary documents as final protocol, incorporating\nall amendments and summaries, the SAP template used to create the SAP and\ninvestigator brochure was handed over to the medical writer. The role of the medical\nwriter was to perform functional QC in terms of content, reliability and\nformat. We ensured that the medical writer provided comments on TLFs prior to\ndatabase lock. Once the SAP was finalized, medical writer drafted CSR without the\ninclusion of actual results and circulated the shell for co-author\u2019s review. Conflicting\ncomments were resolved successfully. After database lock, final TLFs were run\nand handed over to medical writer which included a) final SAP including any\namendments b) Interim analysis findings and c) Approved TLFs in a prescribed\nformat. <\/p>\n\n\n\n An appropriate analysis was carried out, such as descriptive statistics, linear regression analysis with log-transformed data to examine the relationship of dose and AUCs and identify dose linearity. To identify effects due to participant, period and treatment, a cross-over analysis of variance (ANOVA)using log-transformed dose-adjusted AUC and Cmax<\/sub>. Using the pooled residual error and associated degrees of freedom from the ANOVA, the power to detect a 20% difference between treatment means for an alpha level of 0.05 (2-tailed) was calculated. Our medical writer experienced in handling pharmacokinetics came up with a clinical study report accompanied by tables, listing and figures (TLFs) displaying all study data and results with required appendices compliant with International Conference on Harmonization (ICH) E3 (Structure and Content of Clinical Study Reports) guidelines. Our writer ensured to follow standard American Medical Association (AMA) punctuation rules. The report was prepared with a description of the findings of the statistical analyse for the clinical investigation and confirm that the analyses were conducted per the statistical analysis plan. Deviations from the statistical analysis plan or additional unplanned analyses are fully described in the statistical report.<\/p>\n\n\n\n A Case study of Pharmaceutical programming in Preparing CRFs to Tables, Listings and Graphs analysing data of a Single-centre, Randomized, Single-Dose, Open-label, 4-way Cross over study. A leading international pharmaceutical company involved in manufacturing of drugs. The Challenges A pharmaceutical company approached Guires to develop integrated SAP (that includes a detailed description of all patient […]<\/p>\n","protected":false},"author":1,"featured_media":801,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7],"tags":[],"class_list":["post-551","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-case-studies"],"_links":{"self":[{"href":"https:\/\/guires.uk\/newsroom\/wp-json\/wp\/v2\/posts\/551","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/guires.uk\/newsroom\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/guires.uk\/newsroom\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/guires.uk\/newsroom\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/guires.uk\/newsroom\/wp-json\/wp\/v2\/comments?post=551"}],"version-history":[{"count":4,"href":"https:\/\/guires.uk\/newsroom\/wp-json\/wp\/v2\/posts\/551\/revisions"}],"predecessor-version":[{"id":887,"href":"https:\/\/guires.uk\/newsroom\/wp-json\/wp\/v2\/posts\/551\/revisions\/887"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/guires.uk\/newsroom\/wp-json\/wp\/v2\/media\/801"}],"wp:attachment":[{"href":"https:\/\/guires.uk\/newsroom\/wp-json\/wp\/v2\/media?parent=551"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/guires.uk\/newsroom\/wp-json\/wp\/v2\/categories?post=551"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/guires.uk\/newsroom\/wp-json\/wp\/v2\/tags?post=551"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Our Outcomes and Impact<\/h3>\n\n\n\n
Lessons Learned<\/h3>\n\n\n\n