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This project presents a SimBiology implementation of Mager and Jusko’s generic Target-Mediated Drug Disposition model (TMDD) as described in "General pharmacokinetic model for drugs exhibiting target-mediated drug disposition". Target-mediated drug disposition is a common source of nonlinearity in PK profiles for biotherapeutics. Nonlinearities are introduced because drug-target bindings saturate at therapeutic dosing levels.
Drug in the Plasma reversibly binds with the unbound Target to form drug-target Complex. kon and koff are the association and dissociation rate constants, and clearance of free Drug and Complex from the Plasma is described by first-order processes with rate constants, kel and km, respectively. Free target turnover is described by a zero-order synthesis rate, ksyn, and a first order elimination (rate constant, kdeg). The model also includes an optional Tissue compartment to account for non-specific tissue binding or distribution.
References [1] Mager DE and Jusko WJ (2001) General pharmacokinetic model for drugs exhibiting target-mediated drug disposition. J Pharmacokinetics and Pharmacodynamics 28: 507–532.
This project presents SimBiology model implementation of the systemic Renin-Angiotensin-System that was first developed by Lo et al. and used to investigate the effects of different RAS-modulating therapies. The RAS pathway is crucial for blood pressure and kidney function control as well as a range of other organism-wide functions. The model describes the enzymatic conversion of the precursor protein Angiotensinogen to Angiotensin I and its downstream products Angiotensin 1-7, Angiotensin II and Angiotensin IV. Key pathway effects are triggered by the association of Angiotensin II with the AT1-Receptor. A positive feedback loop connects the Angiotensin II–AT1-Receptor complex with the Angiotensinogen conversion (not shown in the diagram). Enzymatic reactions are modeled as pseudo-unimolecular using enzymatic activities as reaction rates. Degradation reactions are described using protein half-life times. Drug pharmacodynamics are included in the model using the term (1-DrugEffect), where DrugEffect follows a sigmoidal dependence on the Drug concentration, to modify the target enzyme activity.
References [1] Lo, A., Beh, J., Leon, H. D., Hallow, M. K., Ramakrishna, R., Rodrigo, M., & Sarkar, A. (2011). Using a Systems Biology Approach to Explore Hypotheses Underlying Clinical Diversity of the Renin Angiotensin System and the Response to Antihypertensive Therapies. Clinical Trial Simulations, 1, 457–482.
This project presents a SimBiology implementation of a physiologically-based pharmacokinetic (PBPK) model for trichloroethylene (TCE) and its metabolites. It is based on the article, “A human physiologically based pharmacokinetic model for trichloroethylene and its metabolites, trichloroacetic acid and free trichloroethanol” by Fisher et al. [1].
The human PBPK model for TCE and its metabolites presented here was developed by Fisher et al. [1] in order to assess human health risks associated with low level exposure to TCE. TCE is a commonly used solvent in the automotive and metal industries for vapor degreasing of metal parts. Exposure to TCE has been associated with toxic responses such as cancer formation and brain disorders in rodents and in humans [1]. In this PBPK model, TCE enters the systemic circulation through inhalation. Its disposition is described by a six-compartment model representing the liver, lung, kidney, fat, and slowly perfused and rapidly perfused tissues. In the liver, TCE is metabolized to trichloroacetic acid (TCA) and free trichloroethanol (TCOH-f) via P450-mediated metabolism where a fraction of TCOH-f is converted to TCA. For simplicity, a four-compartment submodel was used to describe the disposition of metabolites, TCA and TCOH-f, in the lung, liver, kidney, and body (muscle). Both metabolites are described to be excreted in the urine. TCOH-f is glucuronidated in the liver, forming glucuronide-bound TCOH (TCOH-b), and excreted in the urine via a saturable process whereas TCA is excreted by a first-order process by the kidney.
Reference: Fisher, J. W., Mahle, D., & Abbas, R. (1998). A human physiologically based pharmacokinetic model for trichloroethylene and its metabolites, trichloroacetic acid and free trichloroethanol. Toxicology and applied pharmacology, 152(2), 339-359.
Hi there! This is kind of an unusual question, but here it goes. I am a big time Matlab enthusiast and I met some of your representatives at Formula Student Germany back in August. There was a booth were your product was showcased but most importantly there was Matlab merchandise such as stickers, rub-on-tattoos and pens with the mathworks logo being handed out. This merchandise is increadibly popular with me and my nerdy friends. But sadly I didnt bring much with me from the event. Is it possible to get ahold some of it? Is it for sale? Are you willing to sponsor some geeky engineering students?
- the names defined as "keywords" do not in themselves involve function calls to publicly visible routines. These keywords currently include 'break', 'case', 'catch', 'classdef', 'continue', 'else', 'elseif', 'end', 'for', 'function', 'global', 'if', 'otherwise', 'parfor', 'persistent', 'return', 'spmd', 'switch', 'try', 'while'. There is no functional form of any of these: for example, one cannot use global(s) to declare the name contained in the variable "s" to be global. (However, you can define an "end" method; https://www.mathworks.com/help/matlab/matlab_oop/object-end-indexing.html )
- scalar numeric double precision real-valued constants are handled at parse time, including unary plus and unary minus in front of them
- scalar numeric double precision constants followed immediately by "i" or "j" create a complex-value constant at parse time, including unary plus and unary minus in front of them
- whether a complete complex constant with real and imaginary part is handled at parse time is unknown
- literal character vectors and string objects are handled at parse time
- in sufficiently new versions, int64() and uint64() around an integer constant is handled at parse time. This was a change from previous versions which handled it at run time (after the integer had been converted to double precision...)
- whether any other casts such as uint16() or logical() are now handled at parse time is unknown
- assignment of a compete variable (no indexing, no substructure references, etc.) to a plain variable (no indexing, no substructure references, etc.) does not involve any function calls to publicly visible routines (unless I have overlooked a case involving objects)
- "if" or "while" applied to a scalar logical constant or to a scalar logical variable does not involve any function calls to publicly visible routines. However, it is not known whether there is any method to construct a logical value without calling a MATLAB routine: "true" and "false" are MATLAB routines, not constants, and logical() of a numeric constant might be handled at run time
- "for" in which the range is named as a scalar constant or scalar variable do not involve any function calls to publicly visible routines; for example, "for K = 5"
- defining an anonymous function does not involve any function calls to publicly visible routines
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