Software for HEAL Initiative Research
INTRODUCTION
THIS IS A PRE-SOLICITATION NON-COMPETITIVE (NOTICE OF INTENT) SYNOPSIS TO AWARD A CONTRACT OR PURCHASE ORDER WITHOUT PROVIDING FOR FULL OR OPEN COMPETITION (INCLUDING BRAND-NAME).
The National Institutes of Health (NIH), Clinical Center (CC), Office of Purchasing and Contracts (OPC) on behalf of the Department of Critical Care Medicine, Clinical Center (CCMD) at the National Institutes of Health (NIH) intends to negotiate and award a contract without providing for full and open competition (including brand-name) to:
AiCure
19 West 24th Street, 11th Floor
New York, NY 10010
NORTH AMERICAN INDUSTRY CLASSIFICATION SYSTEM (NAICS) CODE
The intended procurement is classified under NAICS code 541512 with a Size Standard $27,500,000.
REGULATORY AUTHORITY
The resultant contract will include all applicable provisions and clauses in effect through the Federal Acquisition Circular (FAC) 2019-06, dated September 10, 2019. This acquisition is conducted under the procedures as prescribed in FAR subpart 13-Simplified Acquisition Procedures at an amount not exceeding the simplified acquisition threshold.
STATUTORY AUTHORITY
This acquisition is conducted under the authority of the Federal Acquisition Regulation (FAR) Part 13-Simplified Acquisition Procedures, Subpart 13.106-1 (b) (1), Soliciting from a single source and is not expected to exceed the simplified acquisition threshold. Contracts awarded using FAR Part 13-Simplified Acquisition Procedures are exempt from the requirements of FAR Part 6-Competition Requirements.
GENERAL INFORMATION
NIH funded HEAL's Initiative (Helping End Addiction Long-Term) for a series of studies aimed at exploring an investigational agent in the treatment of Opioid Use Disorder (OUD) as well as other clinical research within the OUD population and its intersection with infectious disease related morbidity.
AiCure is an artificial intelligence and advanced data analytics company targeting the healthcare industry. Their proprietary intelligent software captures and understands video, audio, and behavioral data to establish the link between patients, disease and treatment. AiCure has tools to help researchers and clinicians understand and predict how patients respond to treatment. Advances in artificial intelligence allow computers to capture physiological datapoints that characterize expressivity, psychomotor function, and cognition.
The goal is to support the development of a medication and adherence reminder system to participants in the NIH's HEAL Initiative supported study titled "SEARCH Safety." For the SEARCH Safety study, the participants will use a phone application platform access adherence for ANS-6637 for 82 subjects. This is a randomized placebo-controlled study to evaluate the safety of ANS-6637 in adults with opioid use disorder with and without opioid agonist therapy.
This study will employ a medication adherence monitoring platform for all subjects in the study. The Platform uses artificial intelligence on smartphones to confirm medication ingestion. In addition, built-in reminders and a communication system allow real-time intervention in case of drug interruptions. Further, the same platform will be used to collect electronic diary information from participants on a daily basis.
The monitoring Platform requires that all patients take each dose of the medication while using a smartphone. The Platform will be provided to patients preloaded on a smartphone, or patients will download the Platform onto their own mobile device during the first visit. The Platform may provide significant benefits to study patients as well as to the researcher team. Study participants will benefit from rapid and tailored intervention in case of non-adherence (drug interruptions) without having to visit the clinic for unscheduled visits. The research team will have access to real-time and continuous adherence data without having to rely on self-reported data or frequent study visits by participants.
Period of Performance 12 months
CONTRACTING WITHOUT PROVIDING FOR FULL OR OPEN COMPETITION (INCLUDING BRAND-NAME) DETERMINATION
The AiCure offering is the only known solution that is able to employ artificial intelligence to confirm and encourage proper medication ingestion by patients, providing an automated, scalable, cost effective and efficient solution for monitoring patients on a population level without any custom hardware, and without any changes to the properties of the medication.
The determination by the Government to award a contract without providing for full and open competition is based upon the market research conducted as prescribed in FAR Part 10-Market Research.
CLOSING STATEMENT
This synopsis is not a request for competitive proposals. However, interested parties may identify their interest and capability to respond to this notice. Responses to this notice shall contain sufficient information to establish the interested parties' bona-fide capabilities for fulfilling the requirement and include a technical proposal, a cost-price proposal, the period of performance, the Dun & Bradstreet Number (DUNS), the Taxpayer Identification Number (TIN), and the certification of business size. All offerors must have an active registration in the System for Award Management (SAM) www.sam.gov.
A determination by the Government not to compete this proposed contract based upon responses to this notice is solely within the discretion of the Government. The information received will normally be consider solely for the purposes of determining whether to proceed on a non-competitive basis or to conduct a competitive procurement.
All responses must be received by September 23, 2019, 1:00 PM Eastern time and must reference solicitation number 19-016988. Responses may be submitted electronically to the Contracting Officer on this announcement. Fax responses will not be accepted.
"All responsible sources may submit a capability statement, proposal, or quotation, which shall be considered by the agency."
Susan Nsangou, Chief, Office of Purchasing and Contracts, Phone 3014969351, Email susan.nsangou@nih.gov
