Rapid response modeling of SARS-CoV-2 transmission

What can modelers learn from recent history to help prepare for the next pandemic?

Structural identifiability analysis of age-structured PDE epidemic models

Computational and mathematical models rely heavily on estimated parameter values for model development. Identifiability analysis determines how well the parameters of a model can be estimated from experimental data. Identifiability analysis is crucial for interpreting and determining confidence in model parameter values and to provide biologically relevant predictions. Structural identifiability analysis, in which one assumes data to be noiseless and arbitrarily fine-grained, has been extensively studied in the context of ordinary differential equation (ODE) models, but has not yet been widely explored for age-structured partial differential equation (PDE) models. These models present additional difficulties due to increased number of variables and partial derivatives as well as the presence of boundary conditions. In this work, we establish a pipeline for structural identifiability analysis of age-structured PDE models using a differential algebra framework and derive identifiability results for specific age-structured models. We use epidemic models to demonstrate this framework because of their wide-spread use in many different diseases and for the corresponding parallel work previously done for ODEs. In our application of the identifiability analysis pipeline, we focus on a Susceptible-Exposed-Infected model for which we compare identifiability results for a PDE and corresponding ODE system and explore effects of age-dependent parameters on identifiability. We also show how practical identifiability analysis can be applied in this example.

Has the relationship between wealth and HIV risk in Sub-Saharan Africa changed over time? A temporal, gendered and hierarchical analysis

This study examines the relationship between wealth and HIV infection in Sub-Saharan Africa to determine whether and how this relationship has varied over time, within and across countries, by gender, and urban environment. The analysis draws on DHS and AIS data from 27 Sub-Saharan African countries, which spanned the 14 years between 2003 and 2016. We first use logistic regression analyses to assess the relationship between individual wealth, HIV infection and gender by country and year stratified on urban environment. We then use meta-regression analyses to assess the relationship between country level measures of wealth and the odds of HIV infection by gender and individual level wealth, stratified on urban environment. We find that there is a persistent and positive relationship between wealth and the odds of HIV infection across countries, but that the strength of this association has weakened over time. The rate of attenuation does not appear to differ between urban/rural strata. Likewise, we also find that these associations were most pronounced for women and that this relationship was persistent over the study period and across urban and rural strata. Overall, our findings suggest that the relationship between wealth and HIV infection is beginning to reverse and that in the coming years, the relationship between wealth and HIV infection in Sub-Saharan Africa may more clearly mirror the predominant global picture.

Measuring office workplace interactions and hand hygiene behaviors through electronic sensors: A feasibility study

Office-based workplaces are an important but understudied context for infectious disease transmission. We examined the feasibility of two different sensors (Opos and Bluetooth beacons) for collecting person-to-person contacts and hand hygiene in office-based workplaces. Opo is an interaction sensor that captures sensor-to-sensor interactions through ultrasonic frequencies, which correspond to face-to-face contacts between study participants. Opos were additionally used to measure hand hygiene events by affixing sensors to soap and alcohol-based hand sanitizer dispensers. Bluetooth beacons were used in conjunction with a smartphone application and recorded proximity contacts between study participants. Participants in two office sites were followed for one-week in their workplace in March 2018. Contact patterns varied by time of day and day of the week. Face-to-face contacts were of shorter mean duration than proximity contacts. Supervisors had fewer proximity contacts but more face-to-face contacts than non-supervisors. Self-reported hand hygiene was substantively higher than sensor-collected hand hygiene events and duration of hand washing events was short (median: 9 seconds, range: 2.5-33 seconds). Given that office settings are key environments in which working age populations spend a large proportion of their time and interactions, a better characterization of empirical social networks and hand hygiene behaviors for workplace interactions are needed to mitigate outbreaks and prepare for pandemics. Our study demonstrates that implementing sensor technologies for tracking interactions and behaviors in offices is feasible and can provide new insights into real-world social networks and hygiene practices. We identified key social interactions, variability in hand hygiene, and differences in interactions by workplace roles. High-resolution network data will be essential for identifying the most effective ways to mitigate infectious disease transmission and develop pandemic preparedness plans for the workplace setting.

Predicting the second wave of COVID-19 in Washtenaw County, MI

The COVID-19 pandemic has highlighted the patchwork nature of disease epidemics, with infection spread dynamics varying wildly across countries and across states within the US. To explore this issue, we study and predict the spread of COVID-19 in Washtenaw County, MI, which is home to University of Michigan and Eastern Michigan University, and in close proximity to Detroit, MI, a major epicenter of the epidemic in Michigan. We apply a discrete and stochastic network-based modeling framework allowing us to track every individual in the county. In this framework, we construct contact networks based on synthetic population datasets specific for Washtenaw County that are derived from US Census datasets. We assign individuals to households, workplaces, schools, and group quarters (such as prisons or long term care facilities). In addition, we assign casual contacts to each individual at random. Using this framework, we explicitly simulate Michigan-specific government-mandated workplace and school closures as well as social distancing measures. We perform sensitivity analyses to identify key model parameters and mechanisms contributing to the observed disease burden in the three months following the first observed cases of COVID-19 in Michigan. We then consider several scenarios for relaxing restrictions and reopening workplaces to predict what actions would be most prudent. In particular, we consider the effects of 1) different timings for reopening, and 2) different levels of workplace vs. casual contact re-engagement. We find that delaying reopening does not reduce the magnitude of the second peak of cases, but only delays it. Reducing levels of casual contact, on the other hand, both delays and lowers the second peak. Through simulations and sensitivity analyses, we explore mechanisms driving the magnitude and timing of a second wave of infections upon re-opening. We find that the most significant factors are workplace and casual contacts and protective measures taken by infected individuals who have sought care. This model can be adapted to other US counties using synthetic population databases and data specific to those regions.

Stigmatizing policies’ influence on HIV risk through their effect on internalized homonegativity and health behaviors among men who have sex with men in Europe

Background

Men who have sex with men (MSM) in Europe are most affected by HIV disparities. Complex systems theory proposes that many health behaviors and risks arise from numerous cascading and interacting processes. Our aim was to explore how stigmatizing policies at the European country-level create pathways to HIV risk and disparities among MSM in Europe.

Methods

We used data from the 2017 European Men Who Have Sex with Men Internet Survey (EMIS-2017). The anonymous online survey recruited 126,090 European MSM. We assessed condom use with steady & non-steady partners as the outcome. Condom use was categorized from zero to 10 (10 or more partners). Abuse was scored zero to three and internalized homonegativity from zero to six. We used the International Gay and Lesbian Association's Rainbow Index as the main predictor, which ranks European countries' laws and policies regarding LGBTQ+ legal protections from zero (worst) to 100 (best). We used structural equation and multi-level modeling for analyses.

Results

The mean Rainbow Index score was 50.8 with a range from 6 to 88. The Rainbow Index scores were the highest in Western European (mean=62.5), then Central European (mean=45.9), then Eastern Europe (mean=21.4) (p < 0.000). Unadjusted regression models suggested that for every one-unit improvement in the Rainbow Index the number of condomless sexual acts with steady sexual partners was reduced [β=-0.0012, 95% CI (-0.0016, -0.0009)]. The unadjusted structural equation model showed that the relationship between the Rainbow Index and condom use with steady partners was mediated by 30% because of internalized homonegativity (p < 0.000).

Conclusions

The policy context influences HIV risk, especially through the policies' effects on condom use. HIV research and prevention efforts must recognize that structural determinants can shape people's risk for HIV and that the best individual and local efforts may be undermined by structural factors such as policies.

Introducing BAIT (Biofilm Architecture Inference Tool): a software program to evaluate the architecture of oral multi-species biofilms

Biofilm model systems are used to study biofilm growth and predict the effects of anti-biofilm interventions within the human oral cavity. Many in vitro biofilm model systems use a confocal laser scanning microscope (CLSM) in conjunction with image analysis tools to study biofilms. The aim of this study was to evaluate an in-house developed image analysis software program that we call BAIT (Biofilm Architecture Inference Tool) to quantify the architecture of oral multi-species biofilms following anti-biofilm interventions using a microfluidic biofilm system. Differences in architecture were compared between untreated biofilms and those treated with water (negative control), sodium gluconate ('placebo') or stannous fluoride (SnF2). The microfluidic system was inoculated with pooled human saliva and biofilms were developed over 22 h in filter-sterilized 25 % pooled human saliva. During this period, biofilms were treated with water, sodium gluconate, or SnF2 (1000, 3439 or 10 000 p.p.m. Sn2+) 8 and 18 h post-inoculation. After 22 h of growth, biofilms were stained with LIVE/DEAD stain, and imaged by CLSM. BAIT was used to calculate biofilm biovolume, total number of objects, surface area, fluffiness, connectivity, convex hull porosity and viability. Image analysis showed oral biofilm architecture was significantly altered by 3439 and 10 000 p.p.m. Sn2+ treatment regimens, resulting in decreased biovolume, surface area, number of objects and connectivity, while fluffiness increased (P<0.01). In conclusion, BAIT was shown to be able to measure the changes in biofilm architecture and detects possible antimicrobial and anti-biofilm effects of candidate agents.

Analytical and computational study of an individual-based network model for the spread of heavy drinking

Two simple models for the spread of heavy drinking among a network of individuals are re-introduced and analysed. We provide theorems on the spread of alcohol abuse for these models in cases involving simple connection schemes. Indicators for this spread that resemble the [Formula: see text] used in disease assessment are suggested and studied. We further provide computations with our models on general application networks and begin to study the reliability of the spread indicators.

Clostridium difficile shows no trade-off between toxin and spore production within the human host

PURPOSE

This study aimed to describe the correlation between Clostridium difficile spore and toxin levels within the human host. In addition, we assessed whether overgrowth of Candida albicans modified this association.

METHODOLOGY

We measured toxin, spore and Candida albicans levels among 200 successively collected stool samples that tested positive for C. difficile, and PCR ribotyped these C. difficile isolates. Analysis of variance and linear regression were used to test the association between spore and toxin levels. Kruskal-Wallis tests and t-tests were used to compare the association between spore or toxin levels and host, specimen, or pathogen characteristics.

RESULTS

C. difficile toxin and spore levels were positively associated (P<0.001); this association did not vary significantly with C. albicans overgrowth [≥5 logs of C. albicans colony-forming units (c.f.u.) g^-1]. However, ribotypes 027 and 078-126 were significantly associated with higher levels of toxin and spores, and C. albicans overgrowth.

CONCLUSION

The strong positive association observed between in vivo levels of C. difficile toxin and spores suggests that patients with more severe C. difficile infections may have increased spore production, enhancing C. difficile transmission. Although, on average, spore levels were higher in toxin-positive samples than in toxin-negative/PCR-positive samples, spores were found in almost all toxin-negative samples. The ubiquity of spore production among toxin-negative and formed stool samples emphasizes the importance of following infection prevention and control measures for all C. difficile-positive patients during their entire hospital stay.

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.

Identifiability Results for Several Classes of Linear Compartment Models

Identifiability concerns finding which unknown parameters of a model can be estimated, uniquely or otherwise, from given input-output data. If some subset of the parameters of a model cannot be determined given input-output data, then we say the model is unidentifiable. In this work, we study linear compartment models, which are a class of biological models commonly used in pharmacokinetics, physiology, and ecology. In past work, we used commutative algebra and graph theory to identify a class of linear compartment models that we call identifiable cycle models, which are unidentifiable but have the simplest possible identifiable functions (so-called monomial cycles). Here we show how to modify identifiable cycle models by adding inputs, adding outputs, or removing leaks, in such a way that we obtain an identifiable model. We also prove a constructive result on how to combine identifiable models, each corresponding to strongly connected graphs, into a larger identifiable model. We apply these theoretical results to several real-world biological models from physiology, cell biology, and ecology.

Abstract P2-10-16: Quantitative HER3 protein expression and PIK3CA mutation status in matched samples from primary and metastatic breast cancer tissues and correlation with time to recurrence

Background: HER3 is thought to play a prominent role in resistance to HER2-directed breast cancer therapies. Recent data suggest that HER3 levels also influence HER2-normal breast tumor biology. HER3 and PI3K signaling are linked in that in HER3 signaling activates PI3K and inhibition of PI3K activity can upregulate HER3 expression. Here, we measured quantitative HER3 protein expression levels and PIK3CA mutation status in matched tissues from the primary tumor and site of metastasis to assess correlations with time to recurrence.

Methods: 44 pairs (8 HER2+ by HERmark®) of matched tissues from the primary tumor and the site of metastasis were evaluated for HER3 protein expression using a sensitive, quantitative assay for HER3 protein expression in FFPE tissue sections (VeraTag®). Matched samples were also evaluated for quantitative HER2 expression (HERmark) and for PIK3CA mutations at exon 9 (E542K and E545K) and exon 20 (H1047R).

Results: HER3 protein expression at the metastatic site was largely independent of HER3 levels at the primary site (Spearman p = 0.50) in contrast to HER2 expression (Spearman p = 0.0004). HER3 expression in the primary tumor correlated with time to recurrence (TTR) (HR = 2.0 per 2-fold increase in HER3; p &lt; 0.0001). Conversely, HER3 expression measured at the site of metastasis was not correlated with TTR (p = 0.55). Estrogen receptor negative tumors were less likely to have PIK3CA mutations (p = 0.023). In cases of primary tumors with PIK3CA mutations, no reversions to wild-type PIK3CA were observed in the metastatic sites. In metastatic tumors, mutations detected in the primary tumor as well as new mutations were observed. A gain of an exon 9 mutation at the metastatic site correlated with shorter TTR (HR = 2.5; p = 0.043). Excluding the 8 samples that were HER2+ by HERmark, longer TTR was observed for patients with PIK3CA mutations in the primary tumor (HR = 0.47; p = 0.042), which is consistent with previous reports. Interestingly, the longer TTR for those with PIK3CA mutations appeared to be dependent on quantitative HER3 protein level (interaction p = 0.065).

Conclusions: HER3 protein expression in matched primary and metastatic breast cancer tissues were unrelated. This may indicate that HER3 protein is influenced by the different tumor microenvironments of the primary and metastatic sites. PIK3CA mutations were either maintained or acquired at metastatic sites. Both low HER3 protein expression and the presence of PIK3CA mutations in the primary tumor but not the metastatic tumor were associated with longer TTR. These observations suggest that HER3 protein expression may be an important prognostic factor for breast cancer progression.

Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P2-10-16.

Latino values in the context of palliative care: illustrative cases from the Family Focused Grief Therapy trial

BACKGROUND

Clinicians meet a variety of ethnicities among patients and families in hospice programs. This article focuses on Latino families.

METHODS

Within a controlled trial of family therapy in the context of palliative care, 17 families identified as Hispanic. Five were examined qualitatively herein.

RESULTS

A synopsis of each family's narrative is presented here. Patterns of strong family loyalty (Familismo), the gender roles of Machismo and Marianismo, the importance of family tradition, expectations about caregiving, and the place of faith and religion emerged as prominent and able potentially to impact on the therapy.

CONCLUSIONS

Family therapists need to be thoughtful about cultural issues as they strive to support families.

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.

Biomedical engineering education through global engineering teams

Most industrial projects require a team of engineers from a variety of disciplines. The team members are often culturally diverse and geographically dispersed. Many students do not acquire sufficient skills from typical university courses to function efficiently in such an environment. The Global Engineering Teams (GET) programme was designed to prepare students such a scenario in industry. This paper discusses five biomedical engineering themed projects completed by GET students. The benefits and success of the programme in educating students in the field of biomedical engineering are discussed.

Cholera epidemic in Haiti, 2010: using a transmission model to explain spatial spread of disease and identify optimal control interventions

BACKGROUND

Haiti is in the midst of a cholera epidemic. Surveillance data for formulating models of the epidemic are limited, but such models can aid understanding of epidemic processes and help define control strategies.

OBJECTIVE

To predict, by using a mathematical model, the sequence and timing of regional cholera epidemics in Haiti and explore the potential effects of disease-control strategies.

DESIGN

Compartmental mathematical model allowing person-to-person and waterborne transmission of cholera. Within- and between-region epidemic spread was modeled, with the latter dependent on population sizes and distance between regional centroids (a "gravity" model).

SETTING

Haiti, 2010 to 2011.

DATA SOURCES

Haitian hospitalization data, 2009 census data, literature-derived parameter values, and model calibration.

MEASUREMENTS

Dates of epidemic onset and hospitalizations.

RESULTS

The plausible range for cholera's basic reproductive number (R(0), defined as the number of secondary cases per primary case in a susceptible population without intervention) was 2.06 to 2.78. The order and timing of regional cholera outbreaks predicted by the gravity model were closely correlated with empirical observations. Analysis of changes in disease dynamics over time suggests that public health interventions have substantially affected this epidemic. A limited vaccine supply provided late in the epidemic was projected to have a modest effect.

LIMITATIONS

Assumptions were simplified, which was necessary for modeling. Projections are based on the initial dynamics of the epidemic, which may change.

CONCLUSION

Despite limited surveillance data from the cholera epidemic in Haiti, a model simulating between-region disease transmission according to population and distance closely reproduces reported disease patterns. This model is a tool that planners, policymakers, and medical personnel seeking to manage the epidemic could use immediately.

Acute anti-emetic withdrawal associated with a hemorrhagic cerebellar arteriovenous malformation

We present a 67-year-old right-handed male with a brachium pontis arteriovenous malformation on continuous anti-emetic therapy who demonstrated acute withdrawal symptoms after the abrupt discontinuation of ondansetron, a 5-HT(3) receptor antagonist. Removal of anti-emetic therapy led to the development of extreme flushing and tremor, but subsequent return of ondansetron resulted in the resolution of these symptoms. This is the first clinical report demonstrating acute withdrawal from an anti-emetic agent and we further highlight the need for future studies evaluating not only arterial supply with pressure gradients and anatomical location, but also the association with periventricular venous drainage, venous drainage stenosis, and mass effect from venous stasis as this may contribute partly to the sensitivity of the serotonergic receptors seen here.

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.

L-T4 bioequivalence and hormone replacement studies via feedback control simulations

FDA Guidance for testing bioequivalence of levothyroxine (L-T(4)) preparations has been challenged by several groups, based on multiple issues. The efficacy of single versus combined hormone therapy also is receiving additional scrutiny. To examine these concerns, we developed a new nonlinear feedback system simulation model of whole-body regulation mechanisms involving dynamics of T(3), T(4), TSH, plasma protein binding, extravascular regulatory enzyme systems, and the hypothalamic-pituitary-thyroid axis, all quantified from human data. To address bioequivalence, we explored how to best account for varying and unmeasured endogenous T(4) following dosing with exogenous oral L-T(4) in euthyroid volunteers in required pharmacokinetic (PK) studies, by simulating various dosing scenarios and developing a new and simple correction method. We computed and assessed dosing error effects and baseline corrections using simulator-predicted endogenous T(4) level variations, due to actual closed-loop effects, and compared these with approximate corrections computed directly from PK data. Predicted dose-responses were quite linear, and for constant baseline, 7-day half-life, and our new formula-correction methods, we established some bounds on bioequivalent dosages. Simulated replacement after thyroidectomy required 141 microg L-T(4) only to normalize T(3) tissue levels and 162 microg L-T(4) to normalize plasma T(3) levels. A combined dose of approximately 103 microg L-T(4) plus approximately 6 microg T(3) ( approximately 18:1 ratio) was needed to normalize both plasma T(3) and T(4) and average tissue T(3) levels. However, simulated average tissue T(3) levels were normalized with standard L-T(4)-only therapy, and plasma T(3) levels were still within the normal range. We suggest a simple and more accurate correction for endogenous T(4) in PK studies. Current standard L-T(4)-only treatment is supported for routine replacement needs.