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Statistical Approaches in the Development of Digital Therapeutics
Published in Oleksandr Sverdlov, Joris van Dam, Digital Therapeutics, 2023
Oleksandr Sverdlov, Yevgen Ryeznik, Sergei Leonov, Valerii Fedorov
Professor Fedorov is an author of more than 200 publications including several books. His monograph on Theory of Optimal Experiments, Academic Press, is one of the first monographs on optimal experimental design. He is an ASA Fellow, Honorary Professor of Cardiff University, UK, and Adjunct Scholar of University of Pennsylvania, USA, elected member and former Council Member of the International Statistical Institute. In 2018 he initiated and chaired a Special Interest Group on Quantum Computing in Statistics and Machine Learning at American Statistical Association.
Combinatorial and Model-Based Methods in Structuring and Optimizing Cluster Trials
Published in Zoran Antonijevic, Robert A. Beckman, Platform Trial Designs in Drug Development, 2018
Valerii V. Fedorov, Sergei L. Leonov
The allocation of subjects to design support points that provide maximum information with respect to the selected optimality criterion is addressed by model-based optimal experimental design theory; see Fedorov (1972), Atkinson et al. (2007), Berger and Wong (2009), Goos and Jones (2011), Fedorov and Leonov (2013). In what follows we focus on D-criterion.
Preparation and in vitro–in vivo evaluation of QbD based acemetacin loaded transdermal patch formulations for rheumatic diseases
Published in Pharmaceutical Development and Technology, 2022
Ece Özcan Bülbül, Hasan Ali Husseın, Gizem Yeğen, Mehmet Evren Okur, Neslihan Üstündağ Okur, Neşe Buket Aksu
Usually, in Modde 12.1 Pro software, quadratic polynomial experiment design (DoE—Design of Experiments) can be accomplished to comprehend the answer components in more particular and to ensure optimization, predictions, and reach a design space. Within the program, Central composite, Three-level full factorial, Box Behnken, D-Optimal, Onion, etc. strategies are utilized for RSM reviews (Sartorius MODDE ® 12 User Guide 2017; Suciu et al. 2018). In the study, according to the test results applied on D-optimal experimental design, a mathematical model was provided by utilizing the Partial Least Squares (PLS) regression technique for each answer in the statistical module of the Modde. Also, via the study, the validity of the experimental procedure was evaluated utilizing ANOVA as a variance test. A model with an R2 (coefficient of determination) of 0.5 has a relatively low significance for ANOVA. Q2 (predictive power of the model) should be higher than 0.5 for a good model and higher than 0.1 for a significant model. For a good model, also the distinction between Q2 and R2 should be <0.3. The most suitable and precise pointer is Q2. To ensure an experimental setpoint that satisfies various properties was utilized the optimizer role of the program. To discover the best potential answer to an equation that depends on a few operating properties, the optimizer utilizes an examination function (Sartorius MODDE ® 12 User Guide 2017; Jiwa et al. 2021).
Proteomic analysis of synovial fluid: current and potential uses to improve clinical outcomes
Published in Expert Review of Proteomics, 2019
Mandy Jayne Peffers, Aibek Smagul, James Ross Anderson
In recent years there has been a huge increase in the number of publications reporting results using ‘omics’ techniques, principally transcriptomics, genomics, metabolomics and proteomics [175]. One of the challenges this poses is the need to develop multi ‘omic’ integration techniques. Computational integration of these separate datasets can work synergistically, greatly enhancing the information that can be obtained as opposed to analysing them separately. Considering this, various software programs are now available which undertake pathway analysis and multi ‘omics’ data visualisation, generating joint pathway p- values [176–179]. In most cases, an optimal experimental design involves the splitting of samples which are subsequently used for appropriate ‘omics’ studies, termed a ‘split sample study’ design [175].
Optimization of prednisolone-loaded long-circulating liposomes via application of Quality by Design (QbD) approach
Published in Journal of Liposome Research, 2018
Bianca Sylvester, Alina Porfire, Dana-Maria Muntean, Laurian Vlase, Lavinia Lupuţ, Emilia Licarete, Alina Sesarman, Marius Costel Alupei, Manuela Banciu, Marcela Achim, Ioan Tomuţă
Risk assessment was conducted in order to recognize critical attributes that can affect final quality of the product. In order to identify the potential risk factors, Ishikawa diagrams, also known as cause-effect diagrams, were constructed. Three critical quality attributes, liposomal PLP concentration, encapsulation efficiency and particle size were defined and delineated to identify all potential risks. After the risk analysis, six variables were chosen to be further studied and were included in a D-optimal experimental design.