The DoD seeks to develop unbiased behavioral discovery platforms to accelerate the detection of and medical countermeasure development against chemical, biological, radiological, and nuclear (CBRN) threats. These platforms will quantify novel behaviors in preclinical animal models, offering greater sensitivity than current methods, and enable high-throughput evaluation of intervention efficacy with high translational value. The initiative addresses limitations in existing animal model behavioral evaluations, which are unmodernized, insensitive, and prone to variability, hindering rapid threat detection and medical countermeasure development. The project focuses on non-invasive, automated, and high-throughput behavioral profiling technologies that do not require human annotation or surgical procedures. The goal is to detect nuanced novel behaviors in animal models across various physiologies, including toxidromes, neuropsychiatric disorders, and traumatic brain injury, ultimately providing automated and high-throughput behavioral profiling technologies to accelerate the discovery of therapeutics and countermeasures for warfighter protection. Phase I involves developing a prototype for automated detection of novel behaviors in animal models, demonstrating sensitivity, specificity, and reproducibility. Phase II aims to advance this technology, addressing compatibility in areas such as detecting other physiologies, use in aerosolized toxic environments, and high-throughput settings. Phase III will focus on dual-use applications, transitioning the technology into chemical threat assessment pipelines for the DoD and commercial markets for disease study and drug development.

The DoD seeks to develop unbiased behavioral discovery platforms to accelerate the detection and development of medical countermeasures against chemical, biological, radiological, and nuclear (CBRN) threats. These platforms will quantify novel behaviors in preclinical animal models, offering greater sensitivity than current methods and enabling high-throughput evaluation of interventions. The project addresses the limitations of unmodernized, insensitive, and variable animal model behavioral evaluations by leveraging machine learning innovations for sensitive detection of animal behaviors. The desired system must use non-invasive measurements, not require human annotation, identify previously unquantified behavioral responses, outperform state-of-the-art assays, demonstrate increased sensitivity to subclinical doses, integrate multiple behavioral feature spaces, and minimize animal handling. Phases I and II focus on prototype development, refinement, and demonstration, with a clear path to dual-use applications in both DoD chemical and biological defense and commercial disease/drug development markets.

The DoD is seeking to develop unbiased behavioral discovery platforms to accelerate the detection and development of medical countermeasures against chemical, biological, radiological, and nuclear (CBRN) threats. These platforms aim to quantify novel behaviors in preclinical animal models with higher sensitivity and enable high-throughput evaluation of intervention efficacy. Current animal model behavioral evaluations are outdated, insensitive, and prone to variability. The DoD requires non-invasive, automated systems that do not rely on human annotation, can identify previously unquantified behavioral responses, outperform existing assays, and demonstrate increased sensitivity to subclinical doses or presymptomatic disease states. The proposed solutions must integrate multiple behavioral feature spaces and minimize animal handling. Phase I focuses on developing a prototype to detect novel behaviors in one animal model, demonstrating sensitivity, specificity, and reproducibility. Phase II aims to refine the technology, addressing two or more compatibility areas like detecting other physiologies or use in high-throughput settings. Phase III involves transitioning the technology for dual-use applications in DoD chemical and biological defense and commercial markets for disease and drug development.

The DoD seeks proposals for

The DoD seeks proposals for

The DoD seeks to develop unbiased behavioral discovery platforms to accelerate the detection of and development of medical countermeasures against current and future threats. These platforms will quantify novel behaviors in preclinical animal models, enabling high-throughput evaluation of intervention efficacy. The project addresses limitations in current animal model behavioral evaluations, which are unmodernized, insensitive, and variable. It aims to develop sensitive, unbiased platforms for discovering and quantifying animal behavior more quickly and at lower levels of effect, leveraging recent advancements in machine learning. The desired solution must use non-invasive measurements, not require human annotation, identify previously unquantified behavioral responses, outperform state-of-the-art assays in sensitivity, integrate multiple behavioral feature spaces, and minimize animal handling. The technology is applicable to various physiologies, including toxidromes, neuropsychiatric disorders, and traumatic brain injury. Phase I focuses on prototype development and demonstration of sensitivity, specificity, and reproducibility. Phase II aims to advance and refine the technology, addressing compatibility in areas like detecting other physiologies, use in toxic environments, and high-throughput settings. Phase III involves dual-use applications for chemical and biological defense within the DoD and commercial markets for disease study and drug development.

The DoD is seeking to develop unbiased behavioral discovery platforms to accelerate the detection and development of medical countermeasures against chemical, biological, radiological, and nuclear (CBRN) threats. These platforms aim to quantify novel behaviors in preclinical animal models with higher sensitivity than current methods and enable high-throughput evaluation of intervention efficacy. Current animal model behavioral evaluations are unmodernized, insensitive, and highly variable, hindering rapid threat detection and countermeasure development. The proposed solutions must use non-invasive measurements, not require human annotation, identify previously unquantified behavioral responses, outperform existing assays, demonstrate increased sensitivity to subclinical doses, integrate multiple behavioral feature spaces, and minimize animal handling. Phase I focuses on developing a prototype for automated detection of novel behaviors in one animal model, demonstrating sensitivity, specificity, and reproducibility. Phase II involves advancing and refining the technology to address compatibility across different physiologies, toxic environments, high-throughput settings, and animal models. The long-term goal is to provide automated behavioral profiling technologies to protect warfighters, with dual-use applications in both defense and commercial pharmaceutical development.

The DoD is seeking to develop unbiased behavioral discovery platforms to accelerate the detection and development of medical countermeasures against chemical, biological, radiological, and nuclear (CBRN) threats. These platforms will quantify novel behaviors in preclinical animal models, offering greater sensitivity than current methods and enabling high-throughput evaluation of intervention efficacy. The project aims to overcome limitations in current animal model behavioral evaluations, which are often unmodernized, insensitive, and prone to variability. The proposed solutions must use non-invasive measurements, not require human annotation, identify previously unquantified behavioral responses, outperform state-of-the-art assays, and demonstrate increased sensitivity to subclinical doses or presymptomatic disease states. The technology should integrate multiple behavioral feature spaces and minimize animal handling. Phase I focuses on developing a prototype for automated detection of novel behaviors in one animal model, demonstrating sensitivity, specificity, and reproducibility. Phase II will advance the prototype to address at least two areas of compatibility, such as detecting other physiologies or use in high-throughput settings, with the goal of delivering a full-scale prototype for chemical and biodefense response. Phase III will involve transitioning the technology for dual-use applications in DoD chemical and biological defense and commercial markets for disease study and drug development.

The DoD seeks proposals for

The DoD seeks proposals for

The DoD seeks to develop unbiased behavioral discovery platforms to accelerate the detection and development of medical countermeasures against chemical, biological, radiological, and nuclear (CBRN) threats. These platforms will quantify novel behaviors in preclinical animal models, offering higher sensitivity than current methods and enabling high-throughput evaluation of intervention efficacy. The project aims to overcome limitations in current animal behavioral evaluations, which are unmodernized, insensitive, and prone to variability, hindering rapid threat detection. Leveraging recent advances in machine learning, the DoD desires non-invasive, automated systems that identify behavioral responses not previously quantified by human observation, integrate multiple behavioral feature spaces, and minimize animal handling. The technology should demonstrate increased sensitivity to subclinical drug doses or presymptomatic disease states. Phase I focuses on developing a prototype for automated detection of novel behaviors in one animal model, demonstrating sensitivity, specificity, and reproducibility. Phase II aims to advance and refine this technology, addressing compatibility in areas such as detecting other physiologies, use in aerosolized toxic environments, high-throughput settings, and different animal models, with the goal of achieving a TRL of 6. Phase III will focus on dual-use applications for both DoD chemical and biological defense and commercial markets for disease study and drug development.

The DoD is seeking to develop unbiased behavioral discovery platforms to accelerate the detection and development of medical countermeasures against chemical and biological threats. These platforms will quantify novel behaviors in preclinical animal models, offering higher sensitivity than current methods and enabling high-throughput evaluation of intervention efficacy. Current animal model evaluations are unmodernized, insensitive, and prone to variability, hindering rapid threat detection. Recent advancements in machine learning offer potential for more sensitive and objective behavioral detection. The desired solution must use non-invasive measurements, avoid human annotation, identify previously unquantified behaviors, outperform state-of-the-art assays, demonstrate increased sensitivity to subclinical doses, integrate multiple behavioral feature spaces, and minimize animal handling. Phase I focuses on developing a prototype for automated detection of novel behaviors in one animal model, demonstrating sensitivity, specificity, and reproducibility. Phase II will advance this technology, addressing compatibility in areas like detecting other physiologies, use in toxic environments, and high-throughput settings. Phase III aims for dual-use applications in DoD chemical and biological defense and commercial disease and drug development.

The DoD is seeking to develop unbiased behavioral discovery platforms to accelerate the detection and development of medical countermeasures against chemical, biological, radiological, and nuclear (CBRN) threats. Current animal model behavioral evaluations are unmodernized, insensitive, and variable, hindering rapid threat detection. The objective is to quantify novel behaviors in preclinical animal models, enabling high-throughput evaluation of intervention efficacy with high translational value. The proposed solutions must use non-invasive measurements, not require human annotation, identify previously unquantified behavioral responses, outperform state-of-the-art assays, demonstrate increased sensitivity to subclinical drug doses or presymptomatic disease states, integrate multiple behavioral feature spaces, and minimize animal handling. Phase I focuses on prototype development and demonstrating sensitivity, specificity, and reproducibility. Phase II aims to advance and refine the technology, addressing compatibility in areas such as detecting other physiologies, use in aerosolized toxic environments, high-throughput settings, generation of behavioral barcodes, and use in other animal models. Phase III will transition the technology for DoD chemical and biological defense and commercial applications in disease and drug development.

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