Optimized Replacement T4 and T4+T3 Dosing in Male and Female Hypothyroid Patients With Different BMIs Using a Personalized Mechanistic Model of Thyroid Hormone Regulation Dynamics.

Objective: A personalized simulation tool, p-THYROSIM, was developed (1) to better optimize replacement LT4 and LT4+LT3 dosing for hypothyroid patients, based on individual hormone levels, BMIs, and gender; and (2) to better understand how gender and BMI impact thyroid dynamical regulation over time in these patients. Methods: p-THYROSIM was developed by (1) modifying and refining THYROSIM, an established physiologically based mechanistic model of the system regulating serum T3, T4, and TSH level dynamics; (2) incorporating sex and BMI of individual patients into the model; and (3) quantifying it with 3 experimental datasets and validating it with a fourth containing data from distinct male and female patients across a wide range of BMIs. For validation, we compared our optimized predictions with previously published results on optimized LT4 monotherapies. We also optimized combination T3+T4 dosing and computed unmeasured residual thyroid function (RTF) across a wide range of BMIs from male and female patient data. Results: Compared with 3 other dosing methods, the accuracy of p-THYROSIM optimized dosages for LT4 monotherapy was better overall (53% vs. 44%, 43%, and 38%) and for extreme BMI patients (63% vs. ~51% low BMI, 48% vs. ~36% and 22% for high BMI). Optimal dosing for combination LT4+LT3 therapy and unmeasured RTFs was predictively computed with p-THYROSIM for male and female patients in low, normal, and high BMI ranges, yielding daily T3 doses of 5 to 7.5 µg of LT3 combined with 62.5-100 µg of LT4 for women or 75-125 µg of LT4 for men. Also, graphs of steady-state serum T3, T4, and TSH concentrations vs. RTF (range 0%-50%) for untreated patients showed that neither BMI nor gender had any effect on RTF predictions for our patient cohort data. Notably, the graphs provide a means for estimating unmeasurable RTFs for individual patients from their hormone measurements before treatment. Conclusions: p-THYROSIM can provide accurate monotherapies for male and female hypothyroid patients, personalized with their BMIs. Where combination therapy is warranted, our results predict that not much LT3 is needed in addition to LT4 to restore euthyroid levels, suggesting opportunities for further research exploring combination therapy with lower T3 doses and slow-releasing T3 formulations.

Informed consent is poorly documented when obtaining toxicology testing at delivery in a Massachusetts cohort.

BACKGROUND: Positive toxicology testing at delivery can have enormous consequences for birthing persons and their families, including charges of child abuse or neglect and potential loss of custody for the birthing parent. Therefore state and national guidelines stipulate that, clinicians must obtain consent before toxicology testing at delivery. OBJECTIVE: This study aimed (1) to determine clinician documentation of patient consent for peripartum toxicology testing and (2) to characterize the extent to which patient and hospital characteristics were associated with documented consent. STUDY DESIGN: This was a retrospective cohort of individuals who underwent toxicology testing within 96 hours of delivery between April 2016 and April 2020 at 5 affiliated hospitals across Massachusetts. Medical records were reviewed for documentation of clinician intent to obtain maternal toxicology, testing indication, verbal consent to testing, and child protective services involvement. Hierarchical multivariable logistic regression was used to examine the association between patient and hospital characteristics and documentation of verbal consent. RESULTS: Among 60,718 deliveries, 1562 maternal toxicology tests were obtained. Verbal consent for testing was documented in 466 cases (29.8%). Documented consent was lacking across most demographic groups. Consent was no more likely to be documented when a report was filed with child protective services and less likely in cases where the birthing parent lost custody before discharge (P=.003). In our multivariable model, consent was least likely to be documented when a maternal complication (abruption, hypertension, preterm labor, preterm premature rupture of membranes, or intrauterine fetal demise) was the indication for testing (adjusted odds ratio, 0.46; 95% confidence interval, 0.28-0.76). Verbal consent was twice as likely to be documented in delivery hospitals with established consent policies (adjusted odds ratio, 2.10; 95% confidence interval, 1.01-4.37). CONCLUSION: Consent for toxicology testing at delivery seemed to be infrequently obtained on the basis of clinician documentation. Provider education and hospital policies for obtaining informed consent are needed to protect the rights of birthing individuals.

Predicting Optimal Combination LT4 + LT3 Therapy for Hypothyroidism Based on Residual Thyroid Function.

Objective: To gain insight into the mixed results of reported combination therapy studies conducted with levothyroxine (LT4) and liothyronine (LT3) between 1999 and 2016. Methods: We defined trial success as improved clinical outcome measures and/or patient preference for added LT3. We hypothesized that success depends strongly on residual thyroid function (RTF) as well as the LT3 added to sufficient LT4 dosing to normalize serum T4 and TSH, all rendering T3 levels to at least middle-normal range. The THYROSIM app was used to simulate "what-if" experiments in patients and study designs corresponding to the study trials. The app graphically provided serum total (T4) and free (FT4) thyroxine, total (T3) and free (FT3) triiodothyronine, and TSH responses over time, to different simulated LT4 and combination LT4 + LT3 dosage inputs in patients with primary hypothyroidism. We compared simulation results with available study response data, computed RTF values that matched the data, classified and compared them with trial success measures, and also generated nomograms for optimizing dosages based on RTF estimates. Results: Simulation results generated three categories of patients with different RTFs and T3 and T4 levels at trial endpoints. Four trial groups had >20%, four <10%, and five 10-20% RTF. Four trials were predicted to achieve high, seven medium, and two low T3 levels. From these attributes, we were able to correctly predict 12 of 13 trials deemed successful or not. We generated an algorithm for optimizing dosage combinations suitable for different RTF categories, with the goal of achieving mid-range normal T4, T3 and TSH levels. RTF is estimated from TSH, T4 or T3 measurements prior to any hormone therapy treatment, using three new nonlinear nomograms for computing RTFs from these measurements. Recommended once-daily starting doses are: 100 µg LT4 + 10-12.5 µg LT3; 100 µg LT4 + 7.5-10 µg LT3; and 87.5 µg LT4 + 7.5 µg LT3; for <10%, 10-20%, and >20% RTF, respectively. Conclusion: Unmeasured and variable RTF is a complicating factor in assessing effectiveness of combination LT4 + T3 therapy. We have estimated and partially validated RTFs for most existing trial data, using THYROSIM, and provided an algorithm for estimating RTF from accessible data, and optimizing patient dosing of LT4 + LT3 combinations for future combination therapy trials.

Review process for IVIg treatment: Lessons learned from INSIGHTS neuropathy study.

BACKGROUND: This project is an effort to understand how orders for IV immunoglobulin (IVIg) are documented and prescribed by physicians, and subsequently, how they are reviewed by insurance companies for the treatment of immune neuropathies. METHODS: A panel of neuromuscular specialists reviewed case records from 248 IVIg-naive patients whose in-home IVIg infusion treatment was submitted to insurance for authorization. After reviewing a case record, 1 panelist was asked to make a diagnosis and to answer several questions about the treatment. A second panelist reviewed the original record and follow-up records that were obtained for reauthorization of additional treatments and was asked to determine whether the patient had responded to the treatment. RESULTS: Our specialists believed that only 32.2% of 248 patients had an immune neuropathy and were appropriate candidates for IVIg therapy, whereas 46.4% had neuropathies that were not immune mediated. Only 15.3% of cases met electrodiagnostic criteria for a demyelinating neuropathy. Our specialists believed that 36.7% of 128 cases with follow-up records had responded to therapy. In cases in which the initial reviewer had predicted that there would be a response to IVIg, the second reviewer found that 54% had responded. This is compared with a 27% response rate when the first reviewer predicted that there would be no response (p = 0.019). CONCLUSIONS: Our expert review finds that the diagnosis of immune neuropathies made by providers, and subsequently approved for IVIg therapy by payers, is incorrect in a large percentage of cases. If payers include an expert in their review process, it would improve patient selection, appropriate use, and continuation of treatment with this expensive therapeutic agent.

DISTING: A web application for fast algorithmic computation of alternative indistinguishable linear compartmental models.

BACKGROUND AND OBJECTIVES: We describe and illustrate use of DISTING, a novel web application for computing alternative structurally identifiable linear compartmental models that are input-output indistinguishable from a postulated linear compartmental model. Several computer packages are available for analysing the structural identifiability of such models, but DISTING is the first to be made available for assessing indistinguishability. METHODS: The computational algorithms embedded in DISTING are based on advanced versions of established geometric and algebraic properties of linear compartmental models, embedded in a user-friendly graphic model user interface. Novel computational tools greatly speed up the overall procedure. These include algorithms for Jacobian matrix reduction, submatrix rank reduction, and parallelization of candidate rank computations in symbolic matrix analysis. RESULTS: The application of DISTING to three postulated models with respectively two, three and four compartments is given. The 2-compartment example is used to illustrate the indistinguishability problem; the original (unidentifiable) model is found to have two structurally identifiable models that are indistinguishable from it. The 3-compartment example has three structurally identifiable indistinguishable models. It is found from DISTING that the four-compartment example has five structurally identifiable models indistinguishable from the original postulated model. This example shows that care is needed when dealing with models that have two or more compartments which are neither perturbed nor observed, because the numbering of these compartments may be arbitrary. CONCLUSIONS: DISTING is universally and freely available via the Internet. It is easy to use and circumvents tedious and complicated algebraic analysis previously done by hand.

THYROSIM App for Education and Research Predicts Potential Health Risks of Over-the-Counter Thyroid Supplements.

BACKGROUND: Computer simulation tools for education and research are making increasingly effective use of the Internet and personal devices. To facilitate these activities in endocrinology and metabolism, a mechanistically based simulator of human thyroid hormone and thyrotropin (TSH) regulation dynamics was developed and further validated, and it was implemented as a facile and freely accessible web-based and personal device application: the THYROSIM app. This study elucidates and demonstrates its utility in a research context by exploring key physiological effects of over-the-counter thyroid supplements. METHODS: THYROSIM has a simple and intuitive user interface for teaching and conducting simulated "what-if" experiments. User-selectable "experimental" test-input dosages (oral, intravenous pulses, intravenous infusions) are represented by animated graphical icons integrated with a cartoon of the hypothalamic-pituitary-thyroid axis. Simulations of familiar triiodothyronine (T3), thyroxine (T4), and TSH temporal dynamic responses to these exogenous stimuli are reported graphically, along with normal ranges on the same single interface page; and multiple sets of simulated experimental results are superimposable to facilitate comparative analyses. RESULTS AND CONCLUSIONS: This study shows that THYROSIM accurately reproduces a wide range of published clinical study data reporting hormonal kinetic responses to large and small oral hormone challenges. Simulation examples of partial thyroidectomies and malabsorption illustrate typical usage by optionally changing thyroid gland secretion and/or gut absorption rates--expressed as percentages of normal--as well as additions of oral hormone dosing, all directly on the interface, and visualizing the kinetic responses to these challenges. Classroom and patient education usage--with public health implications--is illustrated by predictive simulated responses to nonprescription thyroid health supplements analyzed previously for T3 and T4 content. Notably, it was found that T3 in supplements has potentially more serious pathophysiological effects than does T4--concomitant with low-normal TSH levels. Some preparations contain enough T3 to generate thyrotoxic conditions, with supernormal serum T3-spiking and subnormal serum T4 and TSH levels and, in some cases, with normal or low-normal range TSH levels due to thyroidal axis negative feedback. These results suggest that appropriate regulation of these products is needed.

On finding and using identifiable parameter combinations in nonlinear dynamic systems biology models and COMBOS: a novel web implementation.

Parameter identifiability problems can plague biomodelers when they reach the quantification stage of development, even for relatively simple models. Structural identifiability (SI) is the primary question, usually understood as knowing which of P unknown biomodel parameters p1,…, pi,…, pP are-and which are not-quantifiable in principle from particular input-output (I-O) biodata. It is not widely appreciated that the same database also can provide quantitative information about the structurally unidentifiable (not quantifiable) subset, in the form of explicit algebraic relationships among unidentifiable pi. Importantly, this is a first step toward finding what else is needed to quantify particular unidentifiable parameters of interest from new I-O experiments. We further develop, implement and exemplify novel algorithms that address and solve the SI problem for a practical class of ordinary differential equation (ODE) systems biology models, as a user-friendly and universally-accessible web application (app)-COMBOS. Users provide the structural ODE and output measurement models in one of two standard forms to a remote server via their web browser. COMBOS provides a list of uniquely and non-uniquely SI model parameters, and-importantly-the combinations of parameters not individually SI. If non-uniquely SI, it also provides the maximum number of different solutions, with important practical implications. The behind-the-scenes symbolic differential algebra algorithms are based on computing Gröbner bases of model attributes established after some algebraic transformations, using the computer-algebra system Maxima. COMBOS was developed for facile instructional and research use as well as modeling. We use it in the classroom to illustrate SI analysis; and have simplified complex models of tumor suppressor p53 and hormone regulation, based on explicit computation of parameter combinations. It's illustrated and validated here for models of moderate complexity, with and without initial conditions. Built-in examples include unidentifiable 2 to 4-compartment and HIV dynamics models.

Alternative to Ritt's pseudodivision for finding the input-output equations of multi-output models.

Differential algebra approaches to structural identifiability analysis of a dynamic system model in many instances heavily depend upon Ritt's pseudodivision at an early step in analysis. The pseudodivision algorithm is used to find the characteristic set, of which a subset, the input-output equations, is used for identifiability analysis. A simpler algorithm is proposed for this step, using Gröbner Bases, along with a proof of the method that includes a reduced upper bound on derivative requirements. Efficacy of the new algorithm is illustrated with several biosystem model examples.

Simulation of post-thyroidectomy treatment alternatives for triiodothyronine or thyroxine replacement in pediatric thyroid cancer patients.

BACKGROUND: As in adults, thyroidectomy in pediatric patients with differentiated thyroid cancer is often followed by (131)I remnant ablation. A standard protocol is to give normalizing oral thyroxine (T(4)) or triiodothyronine (T(3)) after surgery and then withdraw it for 2 to 6 weeks. Thyroid remnants or metastases are treated most effectively when serum thyrotropin (TSH) is high, but prolonged withdrawals should be avoided to minimize hypothyroid morbidity. METHODS: A published feedback control system model of adult human thyroid hormone regulation was modified for children using pediatric T(4) kinetic data. The child model was developed from data for patients ranging from 3 to 9 years old. We simulated a range of T(4) and T(3) replacement protocols for children, exploring alternative regimens for minimizing the withdrawal period, while maintaining normal or suppressed TSH during replacement. The results are presented with the intent of providing a quantitative basis to guide further studies of pediatric treatment options. Replacement was simulated for up to 3 weeks post-thyroidectomy, followed by various withdrawal periods. T(4) vs. T(3) replacement, remnant size, dose size, and dose frequency were tested for effects on the time for TSH to reach 25 mU/L (withdrawal period). RESULTS: For both T(3) and T(4) replacement, higher doses were associated with longer withdrawal periods. T(3) replacement yielded shorter withdrawal periods than T(4) replacement (up to 3.5 days versus 7-10 days). Higher than normal serum T(3) concentrations were required to normalize or suppress TSH during T(3) monotherapy, but not T(4) monotherapy. Larger remnant sizes resulted in longer withdrawal periods if T(4) replacement was used, but had little effect for T(3) replacement. CONCLUSIONS: T(3) replacement yielded withdrawal periods about half those for T(4) replacement. Higher than normal hormone levels under T(3) monotherapy can be partially alleviated by more frequent, smaller doses (e.g., twice a day). LT(4) may be the preferred option for most children, given the convenience of single daily dosing and familiarity of pediatric endocrinologists with its administration. Remnant effects on withdrawal period highlight the importance of minimizing remnant size.

Finding identifiable parameter combinations in nonlinear ODE models and the rational reparameterization of their input-output equations.

When examining the structural identifiability properties of dynamic system models, some parameters can take on an infinite number of values and yet yield identical input-output data. These parameters and the model are then said to be unidentifiable. Finding identifiable combinations of parameters with which to reparameterize the model provides a means for quantitatively analyzing the model and computing solutions in terms of the combinations. In this paper, we revisit and explore the properties of an algorithm for finding identifiable parameter combinations using Gröbner Bases and prove useful theoretical properties of these parameter combinations. We prove a set of M algebraically independent identifiable parameter combinations can be found using this algorithm and that there exists a unique rational reparameterization of the input-output equations over these parameter combinations. We also demonstrate application of the procedure to a nonlinear biomodel.

Predicting chemical impacts on vertebrate endocrine systems.

Animals have evolved diverse protective mechanisms for responding to toxic chemicals of both natural and anthropogenic origin. From a governmental regulatory perspective, these protective responses complicate efforts to establish acceptable levels of chemical exposure. To explore this issue, we considered vertebrate endocrine systems as potential targets for environmental contaminants. Using the hypothalamic-pituitary-thyroid (HPT), hypothalamic-pituitary-gonad (HPG), and hypothalamic-pituitary-adrenal (HPA) axes as case examples, we identified features of these systems that allow them to accommodate and recover from chemical insults. In doing so, a distinction was made between effects on adults and those on developing organisms. This distinction was required because endocrine system disruption in early life stages may alter development of organs and organ systems, resulting in permanent changes in phenotypic expression later in life. Risk assessments of chemicals that impact highly regulated systems must consider the dynamics of these systems in relation to complex environmental exposures. A largely unanswered question is whether successful accommodation to a toxic insult exerts a fitness cost on individual animals, resulting in adverse consequences for populations. Mechanistically based mathematical models of endocrine systems provide a means for better understanding accommodation and recovery. In the short term, these models can be used to design experiments and interpret study findings. Over the long term, a set of validated models could be used to extrapolate limited in vitro and in vivo testing data to a broader range of untested chemicals, species, and exposure scenarios. With appropriate modification, Tier 2 assays developed in support of the U.S. Environmental Protection Agency's Endocrine Disruptor Screening Program could be used to assess the potential for accommodation and recovery and inform the development of mechanistically based models.

TSH regulation dynamics in central and extreme primary hypothyroidism.

BACKGROUND: Thyrotropin (TSH) changes in extreme primary hypothyroidism include increased secretion, slowed degradation, and diminished or absent TSH circadian rhythms. Diminished rhythms are also observed in central hypothyroid patients and have been speculated to be a cause of central hypothyroidism. We examined whether TSH secretion saturation, previously suggested in extreme primary hypothyroidism, might explain diminished circadian rhythms in both disorders. METHODS: We augmented and extended the range of our published feedback control system model to reflect nonlinear changes in extreme primary hypothyroidism, including putative TSH secretion saturation, and quantified and validated it using multiple clinical datasets ranging from euthyroid to extreme hypothyroid (postthyroidectomy). We simulated central hypothyroidism by reducing overall TSH secretion and also simulated normal TSH secretion without circadian oscillation, maintaining plasma TSH at constant normal levels. We also utilized the validated model to explore thyroid hormone withdrawal protocols used to prepare remnant ablation in thyroid cancer patients postthyroidectomy. RESULTS: Both central and extreme primary hypothyroidism simulations yielded low thyroid hormone levels and reduced circadian rhythms, with simulated daytime TSH levels low-to-normal for central hypothyroidism and increased in primary hypothyroidism. Simulated plasma TSH showed a rapid rise immediately following triiodothyronine (T(3)) withdrawal postthyroidectomy, compared with a slower rise after thyroxine withdrawal or postthyroidectomy without replacement. CONCLUSIONS: Diminished circadian rhythms in central and extreme primary hypothyroidism can both be explained by pituitary TSH secretion reaching maximum capacity. In simulated remnant ablation protocols using the extended model, TSH shows a more rapid rise after T(3) withdrawal than after thyroxine withdrawal postthyroidectomy, supporting the use of replacement with T(3) prior to (131)I treatment.

An algorithm for finding globally identifiable parameter combinations of nonlinear ODE models using Gröbner Bases.

The parameter identifiability problem for dynamic system ODE models has been extensively studied. Nevertheless, except for linear ODE models, the question of establishing identifiable combinations of parameters when the model is unidentifiable has not received as much attention and the problem is not fully resolved for nonlinear ODEs. Identifiable combinations are useful, for example, for the reparameterization of an unidentifiable ODE model into an identifiable one. We extend an existing algorithm for finding globally identifiable parameters of nonlinear ODE models to generate the 'simplest' globally identifiable parameter combinations using Gröbner Bases. We also provide sufficient conditions for the method to work, demonstrate our algorithm and find associated identifiable reparameterizations for several linear and nonlinear unidentifiable biomodels.

TSH-based protocol, tablet instability, and absorption effects on L-T4 bioequivalence.

BACKGROUND: FDA Guidance for pharmacokinetic (PK) testing of levothyroxine (L-T(4)) for interbrand bioequivalence has evolved recently. Concerns remain about efficacy and safety of the current protocol, based on PK analysis following supraphysiological L-T(4) dosing in euthyroid volunteers, and recent recalls due to intrabrand manufacturing problems also suggest need for further refinement. We examine these interrelated issues quantitatively, using simulated what-if scenarios testing efficacy of a TSH-based protocol and tablet stability and absorption, to enhance precision of L-T(4) bioequivalence methods. METHODS: We use an updated simulation model of human thyroid hormone regulation quantified and validated from data that span a wide range of normal and abnormal thyroid system function. Bioequivalence: We explored a TSH-based protocol, using normal replacement dosing in simulated thyroidectomized patients, switching brands after 8 weeks of full replacement dosing. We simulated effects of tablet potency differences and intestinal absorption differences on predicted plasma TSH, T(4), and triiodothyronine (T(3)) dynamics. Stability: We simulated effects of potency decay and lot-by-lot differences in realistic scenarios, using actual tablet potency data spanning 2 years, comparing the recently reduced 95-105% FDA-approved potency range with the original 90-110% range. RESULTS: A simulated decrease as small as 10-15% in L-T(4) or its absorption generated TSH concentrations outside the bioequivalence target range (0.5-2.5 mU/L TSH), whereas T(3) and T(4) plasma levels were maintained normal. For a 25% reduction, steady-state TSH changed 300% (from 1.5 to 6 mU/L) compared with <25% for both T(4) and T(3) (both within their reference ranges). Stability: TSH, T(4), and T(3) remained within normal ranges for most potency decay scenarios, but tablets of the same dose strength and brand were not bioequivalent between lots and between fresh and near-expired tablets. CONCLUSIONS: A pharmacodynamic TSH-measurement bioequivalence protocol, using normal L-T(4) replacement dosing in athyreotic volunteers, is likely to be more sensitive and safer than current FDA Guidance based on T(4) PK. The tightened 95-105% allowable potency range for L-T(4) tablets is a significant improvement, but otherwise acceptable potency differences (whether due to potency decay or lot-by-lot inconsistencies) may be problematic for some patients, for example, those undergoing high-dose L-T(4) therapy for cancer.

Extensions, validation, and clinical applications of a feedback control system simulator of the hypothalamo-pituitary-thyroid axis.

BACKGROUND: We upgraded our recent feedback control system (FBCS) simulation model of human thyroid hormone (TH) regulation to include explicit representation of hypothalamic and pituitary dynamics, and updated TH distribution and elimination (D&E) parameters. This new model greatly expands the range of clinical and basic science scenarios explorable by computer simulation. METHODS: We quantified the model from pharmacokinetic (PK) and physiological human data and validated it comparatively against several independent clinical data sets. We then explored three contemporary clinical issues with the new model: combined triiodothyronine (T(3))/thyroxine (T(4)) versus T(4)-only treatment, parenteral levothyroxine (L-T(4)) administration, and central hypothyroidism. RESULTS: Combined T(3)/T(4) therapy--In thyroidectomized patients, the L-T(4)-only replacement doses needed to normalize plasma T(3) or average tissue T(3) were 145 microg L-T(4)/day or 165 microg L-T(4)/day, respectively. The combined T(4) + T(3) dosing needed to normalize both plasma and tissue T(3) levels was 105 microg L-T(4) + 9 microg T(3) per day. For all three regimens, simulated mean steady-state plasma thyroid-stimulating hormone (TSH), T(3), and T(4) was within normal ranges (TSH: 0.5-5 mU/L; T(4): 5-12 microg/dL; T(3): 0.8-1.9 ng/mL). Parenteral T(4) administration--800 microg weekly or 400 microg twice weekly normalized average tissue T(3) levels both for subcutaneous (SC) and intramuscular (IM) routes of administration. TSH, T(3), and T(4) levels were maintained within normal ranges for all four of these dosing schemes (1x vs. 2x weekly, SC vs. IM). Central hypothyroidism--We simulated steady-state plasma T(3), T(4), and TSH concentrations in response to varying degrees of central hypothyroidism, reducing TSH secretion from 50% down to 0.1% of normal. Surprisingly, TSH, T(3), and T(4) plasma concentrations remained within normal ranges for TSH secretion as low as 25% of normal. CONCLUSIONS: Combined T(3)/T(4) treatment--Simulated standard L-T(4)-only therapy was sufficient to renormalize average tissue T(3) levels and maintain normal TSH, T(3), and T(4) plasma levels, supporting adequacy of standard L-T(4)-only treatment. Parenteral T(4) administration-TSH, T(3), and T(4) levels were maintained within normal ranges for all four of these dosing schemes (1x vs. 2x weekly, SC vs. IM), supporting these therapeutic alternatives for patients with compromised L-T(4) gut absorption. Central hypothyroidism--These results highlight how highly nonlinear feedback in the hypothalamic-pituitary-thyroid axis acts to maintain normal hormone levels, even with severely reduced TSH secretion.

A two-tiered physiologically based model for dually labeled single-chain Fv-Fc antibody fragments.

Monoclonal antibodies (mAb) are being used at an increasing rate in the treatment of cancer, with current efforts focused on developing engineered antibodies that exhibit optimal biodistribution profiles for imaging and/or radioimmunotherapy. We recently developed the single-chain Fv-Fc (scFv-Fc) mAb, which consists of a single-chain antibody Fv fragment (light-chain and heavy-chain variable domains) coupled to the IgG1 Fc region. Point mutations that attenuate binding affinity to FcRn were introduced into the Fc region of the wild-type scFv-Fc mAb, resulting in several new antibodies, each with a different half-life. Here, we describe the construction of a two-tiered physiologically based pharmacokinetic model capable of simulating the apparent biodistribution of both (111)In- and (125)I-labeled scFv-Fc mAbs, where (111)In-labeled metabolites from degraded (111)In-labeled mAbs tend to become trapped within the lysosomal compartment, whereas free (125)I from degraded (125)I-labeled mAbs is quickly eliminated via the urinary pathway. The different concentration-time profiles of (111)In- and (125)I-labeled mAbs permits estimation of the degradation capacity of each organ and elucidates the dependence of cumulative degradation in liver, muscle, and skin on FcRn affinity and tumor mass. Liver is estimated to account for approximately 50% of all degraded mAb when tumor is small (approximately 0.1 g) and drops to about 35% when tumor mass is larger (approximately 0.3 g). mAb degradation in residual carcass (primarily skin and muscle) decreases from approximately 45% to 16% as FcRn affinity of the three mAb variants under consideration increases. In addition, elimination of a small amount of mAb in the kidneys is shown to be required for a successful fit of model to data.

W3MAMCAT: a world wide web based tool for mammillary and catenary compartmental modeling and expert system distinguishability.

W(3)MAMCAT is a new web-based and interactive system for building and quantifying the parameters or parameter ranges of n-compartment mammillary and catenary model structures, with input and output in the first compartment, from unstructured multiexponential (sum-of-n-exponentials) models. It handles unidentifiable as well as identifiable models and, as such, provides finite parameter interval solutions for unidentifiable models, whereas direct parameter search programs typically do not. It also tutorially develops the theory of model distinguishability for same order mammillary versus catenary models, as did its desktop application predecessor MAMCAT+. This includes expert system analysis for distinguishing mammillary from catenary structures, given input and output in similarly numbered compartments. W(3)MAMCAT provides for universal deployment via the internet and enhanced application error checking. It uses supported Microsoft technologies to form an extensible application framework for maintaining a stable and easily updatable application. Most important, anybody, anywhere, is welcome to access it using Internet Explorer 6.0 over the internet for their teaching or research needs. It is available on the Biocybernetics Laboratory website at UCLA: www.biocyb.cs.ucla.edu.

Role of endosomal trafficking dynamics on the regulation of hepatic insulin receptor activity: models for Fao cells.

Evidence indicates that endosomal insulin receptor (IR) trafficking plays a role in regulating insulin signal transduction. To evaluate its importance, we developed a series of biokinetic models for quantifying activated surface and endosomal IR dynamics from published experimental data. Starting with a published two-compartment Fao hepatoma model, a four-pool model was formulated that depicts IR autophosphorylation after receptor binding, IR endosomal internalization/trafficking, insulin dissociation from and dephosphorylation of internalized IR, and recycling of unliganded, dephosphorylated IR to the plasma membrane. Quantification required three additional data sets, two measured, but unmodeled by the same group. A five-pool model created to include endosomal trafficking of the nonphosphorylated insulin-IR complex was fitted using the same data sets, augmented with another published data set. Creation of a six-pool model added the physiologically relevant dissociation of insulin ligand from the activated endosomal IR. More importantly, all three models, validated against additional data not used in model fitting, predict that, mechanistically, internalization of activated IR is a rate-limiting step, at least under the receptor saturating conditions of the fitting data. This rate includes the transit time to a site where insulin dissociation from and/or dephosphorylation of the IR occurs by docking with protein-tyrosine phosphatases (PTPases), or where a sufficient conformational change occurs in the IR, perhaps due to insulin-IR dissociation, where associated PTPases may complete IR dephosphorylation. Our new models indicate that key events in endosomal IR trafficking have significance in mediating IR activity, possibly serving to regulate insulin signal transduction.