Input estimation for drug discovery using optimal control and Markov chain Monte Carlo approaches

Input estimation is employed in cases where it is desirable to recover the form of an input function which cannot be directly observed and for which there is no model for the generating process. In pharmacokinetic and pharmacodynamic modelling, input estimation in linear systems (deconvolution) is well established, while the nonlinear case is largely unexplored. In this paper, a rigorous definition of the input-estimation problem is given, and the choices involved in terms of modelling assumptions and estimation algorithms are discussed. In particular, the paper covers Maximum a Posteriori estimates using techniques from optimal control theory, and full Bayesian estimation using Markov Chain Monte Carlo (MCMC) approaches. These techniques are implemented using the optimisation software CasADi, and applied to two example problems: one where the oral absorption rate and bioavailability of the drug eflornithine are estimated using pharmacokinetic data from rats, and one where energy intake is estimated from body-mass measurements of mice exposed to monoclonal antibodies targeting the fibroblast growth factor receptor (FGFR) 1c. The results from the analysis are used to highlight the strengths and weaknesses of the methods used when applied to sparsely sampled data. The presented methods for optimal control are fast and robust, and can be recommended for use in drug discovery. The MCMC-based methods can have long running times and require more expertise from the user. The rigorous definition together with the illustrative examples and suggestions for software serve as a highly promising starting point for application of input-estimation methods to problems in drug discovery

Input estimation in nonlinear dynamical systems for drug-discovery applications.

In mathematical modelling for drug discovery, nonparametric methods are an alternative to the more commonly used parametric methods, and have the advantage of requiring fewer modelling assumptions. This thesis considers nonparametric methods for performing input estimation (deconvolution) -- inferring the input to a dynamical system based on measurements of the system’s state. A typical application is to determine the absorption profile of an orally administered drug. Commonly used input-estimation methods are restricted to system models that are linear. This thesis aims to develop and evaluate methods which can be applied to nonlinear systems, and which are additionally able to provide uncertainty estimates. An input-estimation method is considered to be a particular choice of 1) prior, 2) function parameterisation, 3) desired statistical quantity, and 4) estimation algorithm. Two classes of methods have been selected and implemented: direct optimal-control methods and Markov chain Monte Carlo (MCMC) methods. These have been evaluated on two pharmacokinetic and two body-weight modelling applications, using simulated as well as real data. Evaluation was based on several criteria, including accuracy, computational speed, and usability. The results show that the methods can achieve good accuracy, provided that data are relatively densely sampled. Properly applied, optimal-control methods can achieve very high speed, approximately 0.1s for typical problems, at the expense of not providing uncertainty estimates. For MCMC methods, the performance is highly dependent on the method settings as well as on the problem. In many cases, MCMC running times can be significantly reduced by a suitable choice of function parameterisation and sampling method. In all cases, estimation is based on clearly stated, quantifiable assumptions

Naturally occurring radioactivity in some Swedish concretes and their constituents - Assessment by using I-index and dose-model

The reference level for effective dose due to gamma radiation from building materials and constructionproducts used for dwellings is set to 1 mSv per year (EC, 1996, 1999), (CE, 2014). Given the specificconditions presented by the EC in report 112 (1999) considering building and construction materials, anI-index of 1 may generate an effective dose of 1 mSv per year. This paper presents a comparison of theactivity concentrations of 40K, 226Ra and 232Th of aggregates and when these aggregates constitute a partof concrete. The activity concentration assessment tool for building and construction materials, the Iindex,introduced by the EC in 1996, is used in the comparison. A comparison of the I-indices values arealso made with a recently presented dose model by Hoffman (2014), where density variations of theconstruction material and thickness of the construction walls within the building are considered. Therewas a ~16e19% lower activity index in concretes than in the corresponding aggregates. The model byHoffman further implies that the differences between the I-indices of aggregates and the concretes' finaleffective doses are even larger. The difference is due, mainly to a dilution effect of the added cement withlow levels of natural radioisotopes, but also to a different and slightly higher subtracted backgroundvalue (terrestrial value) used in the modeled calculation of the revised I-index by Hoffman (2014). Onlyvery minimal contributions to the annual dose could be related to the water and additives used, due tot heir very low content of radionuclides reported.QC 20210428</p

Growth and optical properties of strained GaAs-GaxIn1-xP core-shell nanowires

We have synthesized GaAs-GaxIn1-xP (0.34 < x < 0.69) core-shell nanowires by metal-organic vapor phase epitaxy. The nanowire core was grown Au-catalyzed at a low temperature (450 degrees C) where only little growth takes place on the side facets. The shell was added by growth at a higher temperature (600 degrees C), where the kinetic hindrance of the side facet growth is overcome. Photoluminescence measurements on individual nanowires at 5 K showed that the emission efficiency increased by 2 to 3 orders of magnitude compared to uncapped samples. Strain effects on the band gap of lattice mismatched core-shell nanowires were studied and confirmed by calculations based on deformation potential theory