Scope and financial impact of unpublished data and unused samples among U.S. academic and government researchers.

Unpublished data and unused samples are common byproducts of research activity, but little is known about the scope and economic impact of their disuse. To fill this knowledge gap, we collected self-reported anonymous survey responses from 301 academic and government scientists from randomly selected institutions. Respondents estimated that they published ∼60% of their data and 95% had unpublished data. Of those collecting specimens, 60% stored unused samples. Systemic and logistical issues were identified as major contributory factors. The median cumulative self-reported estimated value of unused resources per researcher was $28,857, with life science ($36k) and government ($109k) researchers reporting the costliest assets. Using NSF headcounts, we estimated that the current cumulative value of unused resources at universities is approximately $6.2 billion, about 7% of the current annual R&D budget. These findings provide actionable information that can be used by decision makers to reduce obstacles that undermine scientific progress and productivity.

An Idealized Clinicogenomic Registry to Engage Underrepresented Populations Using Innovative Technology.

Current best practices in tumor registries provide a glimpse into a limited time frame over the natural history of disease, usually a narrow window around diagnosis and biopsy. This creates challenges meeting public health and healthcare reimbursement policies that increasingly require robust documentation of long-term clinical trajectories, quality of life, and health economics outcomes. These challenges are amplified for underrepresented minority (URM) and other disadvantaged populations, who tend to view the institution of clinical research with skepticism. Participation gaps leave such populations underrepresented in clinical research and, importantly, in policy decisions about treatment choices and reimbursement, thus further augmenting health, social, and economic disparities. Cloud computing, mobile computing, digital ledgers, tokenization, and artificial intelligence technologies are powerful tools that promise to enhance longitudinal patient engagement across the natural history of disease. These tools also promise to enhance engagement by giving participants agency over their data and addressing a major impediment to research participation. This will only occur if these tools are available for use with all patients. Distributed ledger technologies (specifically blockchain) converge these tools and offer a significant element of trust that can be used to engage URM populations more substantively in clinical research. This is a crucial step toward linking composite cohorts for training and optimization of the artificial intelligence tools for enhancing public health in the future. The parameters of an idealized clinical genomic registry are presented.

Ex Ante Economic Evaluation of Arg389 Genetically Targeted Treatment with Bucindolol versus Empirical Treatment with Carvedilol in NYHA III/IV Heart Failure.

OBJECTIVE: The Beta-Blocker Evaluation Survival Trial showed no survival benefit for bucindolol in New York Heart Association (NYHA) class III/IV heart failure (HF) with reduced ejection fraction, but subanalyses suggested survival benefits for non-Black subjects and Arg389 homozygotes. We conducted an ex ante economic evaluation of Arg389 targeted treatment with bucindolol versus carvidolol, complementing a previous ex ante economic evaluation of bucindolol preceded by genetic testing for the Arg389 polymorphism, in which genetic testing prevailed economically over no testing. METHODS: A decision tree analysis with an 18-month time horizon was performed to estimate the cost effectiveness/cost utility of trajectories of 100%, 50%, and 0% of patients genetically tested for Arg389 and comparing bucindolol with empirical carvedilol treatment as per prior BEST subanalyses. Incremental cost-effectiveness/cost-utility ratios (ICERs/ICURs) were estimated. RESULTS: Race-based analyses for non-White subjects at 100% testing showed a loss of (0.04) life-years and (0.03) quality-adjusted life-years (QALYs) at an incremental cost of $2185, yielding a negative ICER of ($54,625)/life-year and ICUR of ($72,833)/QALY lost; at 50%, the analyses showed a loss of (0.27) life-years and (0.16) QALYs at an incremental cost of $1843, yielding a negative ICER of ($6826)/life-year and ICUR of ($11,519)/QALY lost; at 0%, the analyses showed a loss of (0.33) life-years and (0.30) QALYs at an incremental cost of $1459, yielding a negative ICER of ($4421)/life-year and ICUR of ($4863)/QALY lost. Arg389 homozygote analyses at 100% testing showed incremental gains of 0.02 life-years and 0.02 QALYs at an incremental cost of $378, yielding an ICER of 18,900/life-year and ICUR of $18,900/QALY gained; at 50%, the analyses showed a loss of (0.24) life-years and (0.09) QALYs at an incremental cost of $1039, yielding a negative ICER of ($4329)/life-year and ICUR of ($9336)/QALY lost; at 0%, the analyses showed a loss of (0.33) life-years and (0.30) QALYs at an incremental cost of $1459, yielding a negative ICER of ($4421)/life-year and ICUR of ($4863)/QALY lost. CONCLUSION: This independent ex ante economic evaluation suggests that genetically targeted treatment with bucindolol is unlikely to yield clinicoeconomic benefits over empirical treatment with carvedilol in NYHA III/IV HF.

Pricing methods in outcome-based contracting: δ3: reference-based pricing.

AIMS: Six Delta is a six-dimensional independent platform for outcome-based pricing/contracting. The third dimension (δ3) estimates prices on the basis of international drug price referencing methods. We describe this dimension's methodology and present a proof-of-concept application to the treatment of non-small cell lung cancer (NSCLC) with EGFR mutation with osimertinib. MATERIALS AND METHODS: The reference-based pricing dimension utilizes a six-step method: (1) selecting foreign countries based on a set of four criteria (drug is available in the foreign country, price information is available in the foreign country, foreign countries are members within the organization for Economic Co-operation and Development, pricing methods in the foreign countries involve value assessment); (2) adjusting for exchange rates; (3) generating reference price (RP) scenarios; (4) adjusting with the medical inflation rate; (5) pooling all generated RP scenarios and calculating average and standard deviation (SD); (6) and Monte Carlo Simulation (MCS) to estimate the dimension-specific DSPReference. A proof-of-concept exercise with osimertinib in NSCLC was performed for two hypothetical outcome-based contracts: 1-year (2019-2020) and 2-year (2019-2021). RESULTS: The United Kingdom and Canada met the four criteria. For the osimertinib 1-year contract price, the average of eight RP scenarios, adjusted for inflation by 0.44%, was $8,892 (SD = $2,606) for a 30-day prescription. MCS yielded a DSPReference estimate of $9,395 or -35.72% of the wholesale acquisition cost (WAC) of $14,616. For the 2-year contract, the average, adjusted for inflation by 0.72%, was $8,928 (SD = $2,610). MCS yielded a DSPReference estimate of $9,442 or -35.40% of the WAC of $14,616. CONCLUSIONS: We demonstrated that international price referencing methods can be integrated into our proposed Six Delta platform for outcome-based pricing/contracting.

Pricing methods in outcome-based contracting: δ2: willingness-to-pay-based pricing.

AIMS: Six Delta is a six-dimensional independent platform for outcome-based pricing/contracting. The second dimension (δ2) estimates prices on the basis of four willingness-to-pay (WTP) thresholds. We describe this dimension's methodology and present a proof-of-concept application to the treatment of non-small cell lung cancer (NSCLC) with EGFR mutation with osimertinib. MATERIALS AND METHODS: Eight WTP scenarios based on four levels of real gross domestic product per capita (<1GDP/capita, 1 × GDP/capita, 3 × GDP/capita, and >3 × GDP/capita) and two market conditions (monopolistic versus competitive) were assumed. The incremental cost-utility ratio (ICUR) was applied to differently to both markets. In the monopolistic market, assuming no competitors, the cost/QALY ratio for a drug was used; whereas in the competitive market, assuming competitors, the incremental cost-utility ratio (ICUR) was applied. One-way sensitivity analyses were performed and predictive equations were specified to estimate the prices of treatment for the resulting eight WTP scenarios; for which subsequently the average and standard deviation were calculated. A gamma distribution was specified and Monte Carlo Simulation (MCS) was applied to estimate the dimension-specific price based on WTP (DSPWTP). A proof-of-concept exercise with osimertinib in NSCLC was performed for two hypothetical outcome-based contracts: 1-year (2019-2020) and 2-year (2019-2021). The 2018 wholesale acquisition cost (WAC) of $14,616 (30-day prescription) was used to estimate the DSPWTP for each contract. RESULTS: The 1-year estimates averaged $4,654 (SD=$6,462) and the MCS yielded a DSPWTP of $4,547 or -68.89% of the 2018 WAC for a 30-day prescription. The 2-year estimates averaged $4,7667 (SD=$6,480) with the MCS generating a DSPWTP of $4,704 or -67.82% of the WAC. CONCLUSIONS: We demonstrated that WTP-based methods that include various WTP thresholds and market conditions generate price estimates across these thresholds and market conditions that can be integrated into our proposed Six Delta platform for outcome-based pricing/contracting.

Pricing methods in outcome-based contracting: δ4: safety-based pricing.

AIMS: Six Delta is a six-dimensional independent platform for outcome-based pricing/contracting. The fourth dimension (δ4) estimates prices on the basis of assessments of the safety of the drug using an ex ante analysis based on clinical trial data. We describe this dimension's methodology and present a proof-of-concept application to the treatment of non-small cell lung cancer (NSCLC) with EGFR mutation with osimertinib. MATERIALS AND METHODS: The safety-based pricing dimension utilizes a four-step method: 1) pooling adverse events (AE), standardizing, estimating 95%Cis, and adjusting for time; 2) estimating correction factors and corrected probabilities of AEs; 3) estimating the probability of at least one adverse event (AE) occurring and leading to treatment discontinuation; and 4) estimating ranges for payback percentages and performing Monte Carlo Simulation to estimate a DSPSafety. A proof-of-concept exercise with osimertinib in NSCLC was performed for two hypothetical outcome-based contracts: 1-year (2019-2020) and 2-year (2019-2021). We estimated the DSPSafety based on the grade 3/4 AEs observed for osimertinib and standard of care. The 2018 wholesale acquisition cost (WAC) of osimertinib at $14,616 for a 30-day prescription was used. RESULTS: AEs3/4 were retrieved from the FLAURA trial. In the 1-year contract, the DSPSafety of osimertinib was estimated at $14,627 (or +0.08% the 2018 WAC) for a 30-day prescription. In the 2-year contract, the DSPSafety of osimertinib was estimated at $14,516 (or -0.68% the 2018 WAC) for a 30-day prescription. CONCLUSIONS: We demonstrated that ex ante pricing methods-based paybacks for safety issues leading to treatment discontinuation can be integrated into our proposed Six Delta platform for outcome-based pricing/contracting.

Pricing methods in outcome-based contracting: δ5: risk of efficacy failure-based pricing.

AIMS: Six Delta is a six-dimensional independent platform for outcome-based pricing/contracting. The fifth dimension (δ5) estimates prices on the basis of the risk of efficacy failure of a drug. We describe this dimension's methodology and present a proof-of-concept application to the treatment of non-small cell lung cancer (NSCLC) with EGFR mutation with osimertinib. MATERIALS AND METHODS: The risk of efficacy failure pricing dimension utilizes a seven-step method: (1) defining risk; (2) extracting data; (3) predicting models; (4) performing Monte Carlo Simulation (MCS) to estimate risk of efficacy failure; 5) estimating ranges for a payback; (6) adjusting for medical inflation; and (7) performing Monte Carlo Simulation (MCS) to estimate the DSPRisk of efficacy failure. A proof-of-concept exercise with osimertinib in NSCLC was performed for two hypothetical outcome-based contracts: 1-year (2019-2020) and 2-year (2019-2021). We estimated the risk of efficacy failure for osimertinib in terms of overall and progression-free survival versus standard of care. We used the estimated risk to estimate the price reduction on the wholesale acquisition cost (WAC) for the two hypothetical contracts: a 1-year (2019-2020) and 2-year contract (2019-2021). From this we estimated the DSPRisk of efficacy failure. RESULTS: Based on the risk of OS and PFS efficacy failure for osimertinib in OS and PFS, in the 1-year contract, the DSPRisk of efficacy failure was estimated at $12,652 (or -13.44% the 2018 WAC) for a 30-day prescription. For the 2-year contract (2019-2021), the DSPRisk of efficacy failure was estimated at $13,019 (or -10.93% the 2018 WAC). CONCLUSIONS: We demonstrated that pricing methods based on risk of efficacy failure methods can be integrated into our proposed Six Delta platform for outcome-based pricing/contracting.

Pricing methods in outcome-based contracting: δ6: adherence-based pricing.

AIMS: Six Delta is a six-dimensional independent platform for outcome-based pricing/contracting. The sixth dimension (δ6) estimates prices on the basis of adherence to the prescribed regimen, whereby manufacturers provide payers with adherence-enhancing programs and whereby payers implement these programs and provide adherence data to the manufacturer. We describe this dimension's methodology and present a proof-of-concept application to the treatment of non-small cell lung cancer (NSCLC) with EGFR mutation with osimertinib. MATERIALS AND METHODS: We propose two paybacks based on adherence: in-advance (based on clinical trial data) and in-arrear (based on real-world data). The risk of efficacy failure pricing dimension utilizes a 7-step method: 1) defining efficacy endpoints; 2) extracting data; 3) predicting models; 4) estimating in-advance and in-arrear paybacks; 5) suggesting ranges for in-advance and in-arrear paybacks; 6) adjusting for medical inflation; and 7) performing Monte Carlo Simulation (MCS) to estimate the DSPAdherence. A proof-of-concept exercise with osimertinib in NSCLC was performed for two hypothetical outcome-based contracts: 1-year (2019-2020) and 2-year (2019-2021). The 2018 wholesale acquisition cost (WAC) for a 30-day prescription was used and inflated as needed. Herein, the DSPAdherence is estimated exclusively in terms of in-advance payback because real-world data about osimertinib are not yet available and thus the in-arrear payback cannot yet be estimated. RESULTS: For the 1-year contract, the average price for osimertinib was $13,798 (SD=$1,265) and the DSPAdherence was $13,785 (or -5.69% of the 2018 WAC) for a 30-day prescription. For the 2-year contract, the average price was $12,555 (SD=$2,847) and the DSPAdherence was $12,582 (or -13.92% of the 2018 WAC). CONCLUSIONS: We demonstrated that adherence-based pricing methods can be integrated into our proposed Six Delta platform for outcome-based pricing/contracting. The proof-of-concept exercise needs to be expanded with the in-arrear pricing method based on real world data to be secured.

Pricing methods in outcome-based contracting: δ1: cost effectiveness analysis and cost-utility analysis-based pricing.

AIMS: Six Delta is a six-dimensional independent platform for outcome-based pricing/contracting. The first dimension (δ1) estimates prices on the basis of cost-effectiveness (CEA) and cost-utility analysis (CUA). We describe this dimension's methodology and present a proof-of-concept application to the treatment of non-small cell lung cancer (NSCLC) with EGFR mutation with osimertinib. MATERIALS AND METHODS: CEA and CUA were performed using established methods. Probabilistic sensitivity analyses (PSA) were performed to generate cost-effectiveness acceptability curves (CEAC), specifically the PSA incremental cost-effectiveness (PSA ICER) and incremental cost-utility ratio generated CEACs (PSA ICUR). Price of treatment was estimated at three certainty levels (0%, turning point%, 100%). The marketed drug price at turning point was used to estimate prices at 0% and 100% certainty levels, as per PSA ICER and PSA ICUR-generated CEACs. The resulting prices were pooled, inflated, and simulated by Monte Carlo Simulation (MCS) methods to estimate the dimension-specific price based on CEA and CUA (DSPCEA/CUA). A proof-of-concept exercise with osimertinib in NSCLC was performed for two hypothetical outcome-based contracts: 1-year (2019-2020) and 2-years (2019-2021). RESULTS: Turning points were estimated at the 50% certainty level in both PSA ICER and ICUR-generated CEACS. At these points, the wholesale acquisition cost for osimertinib was $14,616 (30-day prescription); inflated by 0.44% for 1-year and by 0.72% for 2-year contracts. Additional prices at 0% and 100% certainty levels were quantified based on the PSA ICER and ICUR-generated CEACs. The MCS yielded a DSPCEA/CUA of $16,391 for the 1-year contract and a DSPCEA/CUA at $16,677 for the 2-year contract for a 30-day prescription. CONCLUSIONS: We demonstrated that conventional CEA and CUA methods generate price estimates at varying levels of certainty that can be integrated into our proposed Six Delta platform for outcome-based pricing/contracting.

Pricing methods in outcome-based contracting: integration analysis of the six dimensions (6 δs).

AIMS: Six Delta is a six-dimensional independent platform for outcome-based pricing/contracting. The six dimensions have been described separately: (δ1) cost-effectiveness analysis and cost-utility analysis-based pricing; (δ2) willingness-to-pay-based pricing; (δ3) reference-based pricing; (δ4) safety-based pricing; (δ5) risk of efficacy failure-based pricing; and (δ6) adherence-based pricing. The final step is to integrate the various dimension-specific pricing estimates into a composite estimate termed the All-Dimensional Price (ADP). We describe the methodology for this integration and present a proof-of-concept application to the treatment of non-small cell lung cancer (NSCLC) with EGFR mutation with osimertinib. MATERIALS AND METHODS: For better accuracy in estimating the ADP, we used the prices generated from the six dimensions at scenario levels, not at the dimension-specific price (DSP) level. We pooled the price estimates and performed Monte Carlo Simulations (MCS) for the price scenarios generated by the six dimensions. We used the results of the proof-of-concept exercise involving osimertinib in NSCLC with EGFR mutation to estimate the ADP in two hypothetical contracts: 1-year (2019-2020) and 2-year contract (2019-2021). RESULTS: The average of the 30-day prescription estimates from the six dimensions averaged $10,819 (SD=$8,486) for the 1-year contract and $10,730 (SD=$8,500) for the 2-year contract. MCS yielded for the 1-year contract an ADP of $10,959 (or -25.02% the 2018 WAC price) and an ADP for the 2-year contract was $10,788 (or -26.19% the 2018 WAC price). CONCLUSIONS: We demonstrated that the integration of the prices from the six dimensions of the Six Delta platform and market conditions is feasible and yields multidimensional prices estimates to support outcome-based pricing/contracting.

Academic Medical Centers as Innovation Ecosystems: Evolution of Industry Partnership Models Beyond the Bayh-Dole Act.

Innovation ecosystems tied to academic medical centers (AMCs) are inextricably linked to policy, practices, and infrastructure resulting from the Bayh-Dole Act in 1980. Bayh-Dole smoothed the way to patenting and licensing new drugs and, to some degree, medical devices and diagnostic reagents. Property rights under Bayh-Dole provided significant incentive for industry investments in clinical trials, clinical validation, and industrial scale-up of products that advanced health care. Bayh-Dole amplified private investment in biotechnology drug development and, from the authors' perspective, did not significantly interfere with the ability of AMCs to produce excellent peer-reviewed science. In today's policy environment, it is increasingly difficult to patent and license products based on the laws of nature-as the scope of patentability has been narrowed by case law and development of a suitable clinical and business case for the technology is increasingly a gating consideration for licensees. Consequently, fewer academic patents are commercially valuable. The role of technology transfer organizations in engaging industry partners has thus become increasingly complex. The partnering toolbox and organizational mandate for commercialization must evolve toward novel collaborative models that exploit opportunities for future patent creation (early drug discovery), data exchange (precision medicine using big data), cohort assembly (clinical trials), and decision rule validation (clinical trials). These inputs contribute to intellectual property rights, and their clinical exploitation manifests the commercialization of translational science. New collaboration models between AMCs and industry must be established to leverage the assets within AMCs that industry partners deem valuable.

Personalized medicine and Hispanic health: improving health outcomes and reducing health disparities - a National Heart, Lung, and Blood Institute workshop report.

Persons of Hispanic/Latino descent may represent different ancestries, ethnic and cultural groups and countries of birth. In the U.S., the Hispanic/Latino population is projected to constitute 29% of the population by 2060. A personalized approach focusing on individual variability in genetics, environment, lifestyle and socioeconomic determinants of health may advance the understanding of some of the major factors contributing to the health disparities experienced by Hispanics/Latinos and other groups in the U.S., thus leading to new strategies that improve health care outcomes. However, there are major gaps in our current knowledge about how personalized medicine can shape health outcomes among Hispanics/Latinos and address the potential factors that may explain the observed differences within this heterogeneous group, and between this group and other U.S. demographic groups. For that purpose, the National Heart, Lung, and Blood Institute (NHLBI), in collaboration with the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), and the Food and Drug Administration (FDA), held a workshop in which experts discussed (1) potential approaches to study medical treatments and health outcomes among Hispanics/Latinos and garner the necessary evidence to fill gaps of efficacy, effectiveness and safety of therapies for heart, lung, blood and sleep (HLBS) disorders and conditions--and their risk factors; (2) research opportunities related to personalized medicine to improve knowledge and develop effective interventions to reduce health disparities among Hispanics/Latinos in the U.S.; and (3) the incorporation of expanded sociocultural and socioeconomic data collection and genetic/genomic/epigenetic information of Hispanic/Latino patients into their clinical assessments, to account for individual variability in ancestry; physiology or disease risk; culture; environment; lifestyle; and socioeconomic determinants of health. The experts also provided recommendations on: sources of Hispanic/Latino health data and strategies to enhance its collection; policy; genetics, genomics and epigenetics research; and integrating Hispanic/Latino health research within clinical settings.

Health status, perceptions and needs of Hispanics in rural Shelbyville, Kentucky.

This cross-sectional study was completed to characterize the health status, perceptions and needs of Hispanics in Shelbyville, KY, USA. Community Health Workers interviewed 668 Hispanic residents in Shelbyville, KY, USA. Data were collected from 2009 to 2010 and analyzed from 2011 until present. Hispanic immigrants from Mexico and other Central American countries completed the survey. The most common self-reported diseases were allergies, asthma, diabetes, lung disease and cardiovascular disease. High blood pressure and diabetes were the two most common diagnoses among insured, older females. Health education, disease prevention and nutrition were the top health concerns among participants. Deficits in health care infrastructure for this largely transient community may compromise their ability to meet health care needs and concerns. Similar issues may be faced by other disadvantaged Hispanic communities in the continental US and likely to be influenced by anticipated provisions of the Patient Protection and Affordable Care Act.

Culturally-Tailored Education Programs to Address Health Literacy Deficits and Pervasive Health Disparities among Hispanics in Rural Shelbyville, Kentucky.

OBJECTIVES: This investigation was conducted to evaluate the impact of culturally-tailored education on health knowledge among Hispanic residents of rural, Shelbyville, KY. DESIGN: The program identified specific pathways to address health literacy deficits and disparities identified through a community-wide health assessment completed in 2010. RESULTS: A total of 43 Hispanic males who shared deficiencies in community-wide health infrastructure were enrolled in the program. The curriculum included an introductory session followed by five, subject-specific, sessions offered on a weekly basis from February to April 2011. Pre/post-test assessments showed marked improvement in knowledge base for all participants after each session, most notably related to cardiovascular disease, diabetes and metabolic syndrome. The group reconvened in January 2012 for follow-up instruction on cardiovascular disease and diabetes, as well as global assessment of knowledge retention over a nine-month period. Comparisons of pre/post testing in cardiovascular disease and diabetes, as well as global health-related knowledge showed significant gains for all parameters. CONCLUSIONS: Health education programs that embrace perceptions of the community of their own health, and that integrate knowledge into culturally-sensitive education, significantly improved health knowledge among Hispanic residents in rural Kentucky. Such gains may translate into sustainable improvements in health literacy and help reduce health disparities.

Assessment of genetic variation for the LINE-1 retrotransposon from next generation sequence data.

BACKGROUND: In humans, copies of the Long Interspersed Nuclear Element 1 (LINE-1) retrotransposon comprise 21% of the reference genome, and have been shown to modulate expression and produce novel splice isoforms of transcripts from genes that span or neighbor the LINE-1 insertion site. RESULTS: In this work, newly released pilot data from the 1000 Genomes Project is analyzed to detect previously unreported full length insertions of the retrotransposon LINE-1. By direct analysis of the sequence data, we have identified 22 previously unreported LINE-1 insertion sites within the sequence data reported for a mother/father/daughter trio. CONCLUSIONS: It is demonstrated here that next generation sequencing data, as well as emerging high quality datasets from individual genome projects allow us to assess the amount of heterogeneity with respect to the LINE-1 retrotransposon amongst humans, and provide us with a wealth of testable hypotheses as to the impact that this diversity may have on the health of individuals and populations.

Environmental risk factors of disease in the Cameron Park Colonia, a Hispanic community along the Texas-Mexico border.

OBJECTIVES: This report summarizes the results of a cross-sectional study in Cameron Park in 2000-2001 to identify disease prevalence and health concerns among colonia residents and to identify environmental exposures to potentially adverse environmental conditions. RESULTS: Asthma and allergies were among the most prevalent respiratory diseases reported in both adults and children of Cameron Park. Other diseases affecting the community in higher numbers included diabetes and heart disease/high blood pressure. Among children, the most prevalent health conditions were asthma, followed by lung diseases, allergies, and to a lesser degree, skin rashes. CONCLUSIONS: These data can be useful in developing education and intervention programs to address the public health and medical issues impacting residents in the Cameron Park Colonia of Texas.

Meeting report: hazard assessment for nanoparticles--report from an interdisciplinary workshop.

In this report we present the findings from a nanotoxicology workshop held 6-7 April 2006 at the Woodrow Wilson International Center for Scholars in Washington, DC. Over 2 days, 26 scientists from government, academia, industry, and nonprofit organizations addressed two specific questions: what information is needed to understand the human health impact of engineered nanoparticles and how is this information best obtained? To assess hazards of nanoparticles in the near-term, most participants noted the need to use existing in vivo toxicologic tests because of their greater familiarity and interpretability. For all types of toxicology tests, the best measures of nanoparticle dose need to be determined. Most participants agreed that a standard set of nanoparticles should be validated by laboratories worldwide and made available for benchmarking tests of other newly created nanoparticles. The group concluded that a battery of tests should be developed to uncover particularly hazardous properties. Given the large number of diverse materials, most participants favored a tiered approach. Over the long term, research aimed at developing a mechanistic understanding of the numerous characteristics that influence nanoparticle toxicity was deemed essential. Predicting the potential toxicity of emerging nanoparticles will require hypothesis-driven research that elucidates how physicochemical parameters influence toxic effects on biological systems. Research needs should be determined in the context of the current availability of testing methods for nanoscale particles. Finally, the group identified general policy and strategic opportunities to accelerate the development and implementation of testing protocols and ensure that the information generated is translated effectively for all stakeholders.

A stochastic model of gene transcription: an application to L1 retrotransposition events.

A simplified mathematical model of gene transcription is presented based on a system of coupled chemical reactions and a corresponding set of stochastic equations similar to those used in enzyme kinetics theory. The quasi-stationary distribution for the model is derived and its usefulness illustrated with an example of model parameters estimation using sparse time course data on L1 retrotransposon expression kinetics. The issue of model validation is also discussed and a simple validation procedure for the estimated model is devised. The procedure compares model predicted values with the laboratory data via the standard Bayesian techniques with the help of modern Markov-Chain Monte-Carlo methodology.

Toxicity assessment of complex mixtures remains a goal.

One of the initial steps in remediating contaminated environments is to assess the human and ecological health risk associated with exposure to contaminants in a specific medium. Presented here are the results of a five-year study investigating the toxicity of simple and complex mixtures. A series of model compounds and simple mixtures including polycyclic aromatic hydrocarbons (PAHs), pentachlorophenol (PCP), and halogenated aliphatic hydrocarbons (HAHs) were analyzed. Mixture toxicity was studied using microbial genotoxicity assays and cytotoxicity assays with renal and neural cells. The majority of binary mixtures described here induced additive responses. A limited number of samples were identified where binary mixtures induced inhibitory effects. For example, benzo(a)pyrene (BAP) alone induced 30% renal cell death, whereas an equimolar dose of chrysene and BAP only produced 1.6% cellular death. In none of the mixtures tested did the mixture toxicity results deviate from the predicted results by an order of magnitude. The results from testing binary mixtures in this study indicate that the results did not deviate significantly from additivity. Complex mixture results were more difficult to interpret. The toxicity of complex mixtures could not be accurately predicted based on chemical analysis. This could be due to chemical interactions or due to the presence of unidentified chemicals, such as alkyl PAHs or high molecular weight PAHs that are not included in the standard risk assessment procedure. Even though the results from these in vitro studies indicate that additive assumptions will generally be appropriate for binary mixtures similar to the ones tested here, the risk associated with complex mixtures remains a challenge to predict. Before the results of toxicity testing can be used to adjust risk assessment calculations, it is important to fully appreciate the chemical composition and to understand the mechanism of observed chemical interactions in animals chronically exposed to low doses of chemical mixtures. This research was supported by ATSDR Grant no. ATU684505 and NIEHS SBRP Grant no. P42 ES04917.