SOLICITATION NOTICE
R -- Knowledge Synthesis and Integration for Precision Prediction Models for Cancer Treatment Management
- Notice Date
- 7/27/2012
- Notice Type
- Presolicitation
- NAICS
- 541990
— All Other Professional, Scientific, and Technical Services
- Contracting Office
- Department of Health and Human Services, National Institutes of Health, National Cancer Institute, Office of Acquisitions, 6120 Executive Blvd., EPS Suite 600, Rockville, Maryland, 20852
- ZIP Code
- 20852
- Solicitation Number
- NCI-120148-TG
- Archive Date
- 8/28/2012
- Point of Contact
- Terry Galloway, Phone: 301-402-4509, Caren N Rasmussen, Phone: (301) 402-4509
- E-Mail Address
-
gallowaytl@mail.nih.gov, cr214i@nih.gov
(gallowaytl@mail.nih.gov, cr214i@nih.gov)
- Small Business Set-Aside
- N/A
- Description
- Contracting Office Address Department of Health and Human Services, National Institutes of Health, National Cancer Institute, Office of Acquisitions, 6120 Executive Blvd. EPS Room 6074, Rockville, MD, 20852, UNITED STATES Description The National Cancer Institute (NCI), Division of Cancer Control and Population Sciences (DCCPS), Clinical and Translational Epidemiology Branch (CTEB) plans to procure on a sole source basis services to provide knowledge integration for precision prediction models for cancer treatment management from Brown University, 1 Prospect Street, Providence, RI 02912-9079 This acquisition will be processed in accordance with simplified acquisition procedures as stated in FAR Part 13.106-1(b)(1). The North American Industry Classification System code is 541990 and the business size standard is $7.0 million. Only one award will be made as a result of this solicitation. This will be awarded as a firm fixed price type contract. Period of Performance shall be from award through twelve (12) months. It has been determined there are no opportunities to acquire green products or services for this procurement. One of the primary functions of the CTEB is to plan, develop, direct, coordinate, and evaluate a program of epidemiologic research to improve health outcomes by developing and disseminating evidence-based information to patients, clinicians, and other stakeholders, about which interventions are most effective for which patients under specific circumstances. To optimize patient outcomes, oncology healthcare providers require accurate tools which can differentiate between cancer patients that will respond to certain therapies and patients that are at highest risk of cancer progression or recurrence, a new primary cancer, or an adverse event. The decision-making process for cancer treatment management is complex and challenging because it requires balancing the clinical benefit of a treatment regimen with life expectancy, patient values, treatment goals, comorbidities, and potential treatment-related adverse events. Benefit/risk predictive tools are statistical models developed by combining and synthesizing data from clinical trials and observational studies to predict probabilities of outcome(s). Prediction tools have repeatedly been shown to be more accurate at predicting risk than healthcare providers alone and greatly aid and improve informed decision-making on treatment and post-treatment strategies. The tasks for this knowledge integration project are (1) conduct a comprehensive review that would identify, synthesize, and appraise the scientific literature on the analytic validity, clinical validity and clinical utility of peer-reviewed benefit and risk prediction tools for cancer treatment management, (2) determine their utilization of these tools in oncology practice, (3) develop a searchable database that provides a comprehensive, unbiased, centralized, publicly available collection of prediction tools for cancer treatment management, and provide recommendations on what type of future tools are needed by oncologists and their patients to better predict treatment effects. This project requires expertise in molecular epidemiology, genomics, clinical oncology, risk prediction, evidence-based medicine, systematic reviews, and developing online databases and resources. The research at Brown University focuses on systematic review and meta-analysis of clinical research, with a particular emphasis on empirical research and development of novel methodology and software tools. Brown University currently employs Dr. Thomas A. Trikalinos and a team of scientists who are uniquely qualified to perform this work and have had rigorous training in genetic epidemiology, evidence-based medicine, systematic reviews, and developing software tools. Dr. Trikalinos has published more than 90 research articles and book chapters, and 30 peer-reviewed comparative effectiveness reviews, evidence reports and technology assessments in the context of the AHRQ's Effective Healthcare Program. Among his team's recent systematic reviews in the area of cancer genomics and risk prediction include publications involving (1) a systematic review of Anti-epidermal growth factor receptor treatment effect modification by KRAS mutations in advanced colorectal cancer (2011, Ann Intern Med 154: 37-49), (2) an evaluation of BCR-ABL mutation testing to predict response to tyrosine kinase inhibitors in patients with chronic myeloid leukemia (2010, PLoS Curr 2: RRN1204) and (3) a review of pharmacogenomic CYP2D6 testing to predict response to tamoxifen in women with breast cancer (2010, PLoS Curr 2: RRN1176). All of these complex and specialized systematic reviews were commissioned by the Agency of Healthcare Quality (AHRQ) to inform oncology practice and policy and were ultimately presented to the Centers for Medicare and Medicaid Services for considerations of national genetic testing coverage decisions. These studies clearly demonstrate the exceptional and distinctive expertise that Brown University possess in the specialized fields of molecular epidemiology, genomics, clinical oncology, risk prediction, evidence-based medicine, systematic reviews. The NCI is not aware of any other research investigators who could adequately and comprehensively complete the proposed work of this project with the highest level of quality and detail required by the National Cancer Institute. The online database resource which will be developed will be made publically available to researchers worldwide and must be of the highest quality, precision, accuracy and comprehensiveness. This notice is not a request for competitive quotation. However, if any interested party believes it can meet the above requirement, it may submit a statement of capabilities. The statement of capabilities and any other information furnished must be in writing and must contain material in sufficient detail to allow NCI to determine if the party can perform the requirement. Capability statements must be received in the contracting office by 11:00 AM EST, on August 13, 2012. For further information, please contact Terry Galloway, Contract Specialist via electronic mail at gallowaytl@mail.nih.gov. A determination by the Government not to compete this proposed requirement based upon responses to this notice is solely within the discretion of the Government. Information received will be considered solely for the purpose of determining whether to conduct a competitive procurement. No collect calls will be accepted. No faxed or emailed capability statements will be accepted. In order to receive an award, contractors must be registered and have valid certification in the Central Contractor Registration (CCR) and the Online Representations and Certifications Applications (ORCA). Reference: NCI-120148-TG on all correspondence.
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- SN02818120-W 20120729/120727235946-a598e9c709cd10d54af1cf2eeda93eda (fbodaily.com)
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