HR001119S0003.pdf

HR001119S0003 ACCELERATED MOLECULAR DISCOVERY (AMD) 1

Broad Agency Announcement Accelerated Molecular Discovery (AMD)

Defense Sciences Office

HR001119S0003

October 19, 2018

HR001119S0003 ACCELERATED MOLECULAR DISCOVERY (AMD) 2

Table of Contents I. Funding Opportunity Description

A. Introduction B. Background C. Program Description/Scope D. Program Structure E. Schedule/Milestones F. Deliverables G. Government-furnished Property/Equipment/Information H. Other Program Objectives and Considerations

II. Award Information A. General Award Information B. Fundamental Research

III. Eligibility Information A. Eligible Applicants B. Organizational Conflicts of Interest C. Cost Sharing/Matching

IV. Application and Submission Information A. Address to Request Application Package B. Content and Form of Application Submission C. Submission Dates and Times D. Funding Restrictions E. Other Submission Requirements

V. Application Review Information A. Evaluation Criteria B. Review and Selection Process C. Federal Awardee Performance and Integrity Information (FAPIIS)

VI. Award Administration Information A. Selection Notices B. Administrative and National Policy Requirements C. Reporting

VII. Agency Contacts VIII. Other Information

A. Frequently Asked Questions (FAQs) B. Collaborative Efforts/Teaming C. Proposers Day

BAA Attachments:

Attachment A: ABSTRACT SUMMARY SLIDE TEMPLATE Attachment B: ABSTRACT TEMPLATE Attachment C: PROPOSAL SUMMARY SLIDE TEMPLATE Attachment D: PROPOSAL TEMPLATE VOLUME 1 TECHNICAL & MANAGEMENT VOLUME Attachment E: PROPOSAL TEMPLATE VOLUME 2 COST VOLUME Attachment F: COST SUMMARY SPREADSHEET Attachment F-2: PROPOSAL TEMPLATE VOLUME 2 COST BREAKDOWN TEMPLATE (Optional) Attachment G: PROPOSAL TEMPLATE VOLUME 3 ADMINISTRATIVE & NATIONAL POLICY VOLUME

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PART I: OVERVIEW INFORMATION

Federal Agency Name: Defense Advanced Research Projects Agency (DARPA), Defense Sciences Office (DSO)

Funding Opportunity Title: Accelerated Molecular Discovery (AMD)

Announcement Type: Initial Announcement

Funding Opportunity Number: HR001119S0003

Catalog of Federal Domestic Assistance (CFDA) Number(s): 12.910 Research and Technology Development

Dates (All times listed herein are Eastern Time.)

o Posting Date: October 19, 2018 o Proposers Day: October 18, 2018. See Section VIII.C.

o Abstract Due Date: November 1, 2018, 4:00 p.m.

o FAQ Submission Deadline: January 3, 2019, 4:00 p.m. See Section VIII.A.

o Full Proposal Due Date: January 14, 2019, 4:00 p.m.

Types of Instruments that May be Awarded: Procurement contracts, grants, cooperative agreements or Other Transactions

Agency contacts o Technical POC: Anne Fischer, Program Manager, DARPA/DSO o BAA Email: AMD@darpa.mil o BAA Mailing Address:

DARPA/DSO

ATTN: HR001119S0003

675 North Randolph Street Arlington, VA 22203-2114 o DARPA/DSO Opportunities Website: http://www.darpa.mil/work-with-us/opportunities

Teaming Information: See Section VIII.B for information on teaming opportunities.

Frequently Asked Questions (FAQ): FAQs for this solicitation may be viewed on the DARPA/DSO Opportunities Website. See Section VIII.A for further information.

http://www.darpa.mil/work-with-us/opportunities?tFilter=&oFilter=2&sort=name

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PART II: FULL TEXT OF ANNOUNCEMENT

I. Funding Opportunity Description

This Broad Agency Announcement (BAA) constitutes a public notice of a competitive funding opportunity as described in Federal Acquisition Regulation (FAR) 6.102(d)(2) and 35.016 as well as 2 CFR § 200.203. Any resultant negotiations and/or awards will follow all laws and regulations applicable to the specific award instrument(s) available under this BAA, e.g., FAR

15.4 for procurement contracts.

A. Introduction The Defense Sciences Office (DSO) at the Defense Advanced Research Projects Agency (DARPA) is soliciting innovative research proposals in the area of autonomous molecular design to accelerate the discovery, validation, and optimization of new, high-performance molecules for Department of Defense (DoD) needs. DARPA seeks to develop new, systematic approaches to increase the pace of discovery and optimization of high-performance molecules through development of closed-loop systems that exploit, build and integrate tools for: 1) extracting existing data from databases and text; 2) executing autonomous experimental measurement and optimization; and 3) incorporating computational approaches to develop physics-based representations and predictive tools. Such methods will ultimately enable Artificial Intelligence (AI)-based design and discovery of completely new molecules that are optimized across multiple molecular properties for specific DoD needs. Proposed research should investigate innovative approaches that enable revolutionary advances in science, devices, and systems related to small organic molecules. Specifically excluded is research that primarily results in evolutionary improvements to the existing state of practice.

B. Background Efficient discovery and production of new molecules is essential to realize capabilities across the DoD, from simulants and medicines essential to counter emerging threats, to coatings, dyes and specialty fuels needed for advanced performance. Current approaches to develop molecules for a given application are intuition-driven, mired in slow iterative design/test cycles, and ultimately limited by the specific molecular expertise of the chemist, bottlenecks in the synthesis of candidates, and the pace of by-hand validation and optimization of these candidates. Even in industries that exploit high-throughput screening (HTS) of millions of molecules per day, subsequent design, synthesis and testing of molecular analogs is a months-to-years-long process.

Brute force HTS of a common (albeit large) library has yet to yield productivity benefits over chemical intuition and past precedent, which still boasts a success rate well beyond HTS methods.

Ultimately then, it is not just the rate of experiments that matters, but the quality and efficiency of those experiments. Given a potential structure space of ~1060 for pharmacologically relevant molecules alone, with just over 109 molecules of any kind reported to date, the possibilities are seemingly endless, but our current approaches are considerably constraining.

Accelerated Molecular Discovery (AMD) will address these pace and performance shortcomings by creating fundamentally new closed-loop systems that enable rapid design, discovery and optimization of molecules with defined properties. Such systems will exploit, build and integrate tools for: 1) extracting existing data from databases and text; 2) executing autonomous

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experimental measurement and optimization; and 3) incorporating computational approaches to develop physics-based representations and predictive tools. AMD systems will provide a comprehensive computational and experimental means to design, discover, validate, and optimize new molecules, iteratively and actively learning to more efficiently and effectively discover high-performance molecules relevant to national security.

Artificial Intelligence (AI) methods have recently been applied to various aspects of chemistry, including synthetic route design, property prediction, inverse design, and process optimization.

Though some successes have been realized, a number of technical challenges continue to limit the potential of AI in the molecular sciences. The first relates to the data provided to the AI systems, in terms of both the content and accessibility of existing chemical data, and how we currently generate new chemical knowledge. The second centers on representation of this data to AI, or determining what features of a molecular system are necessary to embody chemical character and how to describe them in algorithmically accessible form.

Data:

As suggested above, the sheer volume of data produced by HTS and other methods in the molecular sciences has not been sufficient to provide comparable insights to an expert chemist.

Indeed, the value of new data to an AI model is a function of data already seen by the model, the particular AI model being used, and the task the model is performing. Therefore, an essential question is how to efficiently acquire chemistry data that will prove most valuable to specific AI models and tasks. Existing data in chemistry, like many fields, is sparse, noisy and incomplete.

For example, while we have access to databases containing reaction schemes for nearly 40 million molecules, less than a quarter of those include data on such a basic (and critical) parameter as reaction yield. Moreover, those databases that do report yield are highly biased to high-yield reactions, as chemists report primarily optimized processes in relatively algorithm-accessible reaction schemes. A closer look at the literature, however, reveals that valuable information about reaction failures, lower yield and optimization experiments is often included in algorithm inaccessible form (e.g., text, tables, and figures). Examples relevant to molecular properties that are the subject of this program abound as well, with critical data and metadata present in manuscripts, lab notebooks, etc. Existing tools such as named entity recognition (NER) and semantic role labeling (SRL) in Natural Language Processing (NLP) can identify mentions of terms of interest and relate them in meaningful ways. Tools in the computer vision (CV) community exist that could aid in extracting knowledge from molecular structure diagrams, chemical equations, tables, and figures. Yet, tools from these communities have been sparingly applied to chemistry to augment our chemical knowledge and exploit past experiments.

Perhaps an even greater challenge, however, is developing a means to rapidly generate new data through methods that more efficiently explore a search space, whether it be a query of structural variants to optimize a specific property or a process-level optimization across a series of experimental conditions. While not standard in conventional chemistry laboratories, automated approaches are emerging, including semi-automated analytical feedback systems for property optimization and design-of-experiments (DOE)-like approaches for hands-free optimization of experimental processes. Such approaches, if effectively coupled to AI models through active learning, reinforcement learning, or adversarial learning methods, could generate data that is uniquely valuable to the AI model and task at hand, in terms of both training and validation.

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Moreover, the data generated by automated experimental systems would be objective and complete in a way that is possible only with direct experimental observation. The potential of multi-objective optimization, particularly of multiple properties in a single molecule, makes this nascent application of automation and AI to chemistry even more appealing.

Representation:

Chemists have long represented molecules using static, two-dimensional graphs, where the nodes are atoms and the edges are bonds. These same structure-based features are the dominant descriptors used for training statistical machine learning algorithms. Even when 100s to 1000s of structural features are incorporated into a representation of a molecule, such representations fail to capture known, critical property-dependent elements of a molecular system. Physics-based data, such as molecular dynamics, quantum mechanics, and mechanistic information, would be valuable, but the computation time traditionally required by simulation platforms to generate this data for new molecules hinders its application to AI in chemistry. Perhaps strategies such as machine learning approximations of such physics data could overcome this limitation. Developing AI-based tools to accelerate molecular design and discovery most certainty must incorporate these elements to robustly represent what matters most in molecule-based property prediction. However, the implications of what this means—exactly which physics should be represented, how this should be done, and to what degree it matters in the context of a particular molecular property or domain—is yet unknown.

Addressing these challenges in a meaningful way to provide practical software and hardware tools for molecular design requires development of a closed-loop system. With parallel development and real-time feedback of components for data extraction, data generation, and representations, AI models and optimization frameworks, components can be built, validated, and improved to evaluate their ultimate potential and fundamental limitations for applications in high-performance small molecule design and discovery.

C. Program Description/Scope AMD will increase the pace of molecular discovery and optimization, resulting in tools, techniques and closed-loop systems that design novel molecules with a desired set of properties. Performer teams will develop complete closed-loop systems that exploit, build, and integrate tools for 1) extracting existing data from databases and text; 2) executing autonomous experimental measurement and optimization; and 3) incorporating computational approaches to develop physics-based representations and predictive tools. Tools, models, data, and systems will be transferred to Government teams throughout the program, potentially beginning as early as midway through the base period, for independent validation and verification (IV&V). AMD will emphasize creating and leveraging open source technologies and architectures, making data sharing and collaboration among performers and with Government IV&V teams key aspects of this program. Intellectual property rights asserted by proposers are strongly encouraged to be aligned with open source regimes and be clearly defined in the proposal submission.

AMD is focused on developing closed-loop systems that can measure, model, and predict among a set of fundamental molecular properties that are relevant to molecular function and performance in a given application. Properties of interest include boiling point, vapor pressure, density (including liquids), solubility (e.g., water/lipid), spectral signature (e.g., infrared/Raman), HR001119S0003 ACCELERATED MOLECULAR DISCOVERY (AMD) 7 degradation products, toxicity, and viscosity. Proposers may choose to build systems to measure, model, predict and optimize additional properties, but should select four from this set. Proposals should identify one or more potential applications (e.g., medicines, dyes, agrochemicals, coatings, fuels, etc.) for which their selected set of properties are relevant, as this affects aspects such as available data, target molecular classes, etc. However, performers should focus on developing generalizable systems that enable design of molecules with specific properties that are informed, but not dictated by, an application. Importantly, in addition to tool, model and system validation, Government IV&V teams will assess the feasibility of extending and applying tools developed for one application area to another. Understanding the challenges inherent in transitioning these models and tools among application areas will be a critical aspect of the program.

AMD performers will develop the approaches, methods, and tools to build closed-loop systems.

These systems are divided into three Focus Areas (FAs) that pertain to the technical challenges and development necessary to realize the AMD goals:

FA1: Data extraction from existing sources;

FA2: Data generation via automated experimental platforms; and FA3: Representations, AI models, and optimization frameworks

Proposers must address all three FAs in their proposed approach, resulting in an integrated system that can extract and exploit existing data, generate new data, and develop and validate new molecular representations and optimization frameworks for realizing high fidelity AI models for molecular design and discovery. Given the interdisciplinary nature of the work, teams should be interdisciplinary with a composition including relevant fields such as chemistry, engineering, computer science, and mathematics. Expertise in automation, autonomy, and AI-based representation are highly encouraged. While ultimate scope and implementation of each FA will be dependent on the set of molecular properties and the performer-defined approach, an example implementation of the envisaged FA integration is as follows: FA3 methods identify the optimal data required to improve model performance, the FA1 and FA2 systems acquire or generate the required contextually rich data, this data is transformed into sufficiently descriptive representations accessible to the model, the model is updated based on this new data, and the new model is experimentally validated by FA2 systems and/or Government IV&V teams. This process is repeated, enabling continuous optimization, validation and updates of the model. This general example is not the only viable integration approach and proposers should define an anticipated closed-loop framework through which the developed system will be tested, validated, and improved.

The techniques, data, synthetic approaches, scale, and expertise required to demonstrate AMD goals will vary widely depending on the specific chemistries and proposed properties that will be addressed. In order to justify the selected properties and the applications to which they may be relevant, proposals must identify the need for innovation (i.e., state of the field), existing sources of relevant data, credible quantitative metrics for evaluation of progress (in addition to those specifically enumerated in this BAA), and also describe construction of an appropriate experimental platform relative to current capabilities, expertise, and equipment. Discussion of the generalizability of the selected property set to a broader set of potential applications (i.e., for

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Government IV&V assessment), as well as a detailed discussion on the relevance of proposed measurements, models, and tools should also be included.

Proposers must address any restrictions or barriers to sharing tools, models, data, and/or systems with Government IV&V teams, and anything that would restrict or otherwise hinder an open and effective collaboration. DARPA expects all groups to work openly with Government IV&V teams as required and/or directed throughout the program, and proposals must include a specific task related to the collaboration effort. As mentioned above, intellectual property rights asserted by proposers are strongly encouraged to be aligned with open source regimes.

FA1: Data extraction from existing sources Performers will apply techniques such as natural language processing and computer vision to extract and transform information from sources such as articles, manuscripts, and electronic lab notebooks into formats exploitable by AI models (FA3). Data extraction from both text and imagery sources is required, to include prose, figures, graphs, and tables, as well as directly from analytical instrumentation, as is correlation and fusion of this data across sources. DARPA encourages performers to exploit existing tools and approaches wherever possible. Development of novel methods is acceptable, if existing tools will not meet the performance metrics described in Section E, or are not compatible with other components of the proposed AMD closed-loop system. Proposals should fully describe the data sources that will be used during the AMD period of performance, and in particular, comment on existing formats and accessibility, to include if annotations and labels to enable evaluation as described in Section E are present or if such annotation will occur during the program. Performers should not rely on DARPA or Government IV&V teams to provide data for tool development, evaluation, validation, or system design. The data output of FA1 tools should complement that produced by automated experimental platforms (FA2) in developing and optimizing AI models (FA3).

FA2: Development of autonomous experimental platforms Performers will develop and integrate the control software, reaction and robotics hardware, and instrumentation necessary to enable autonomous experimentation. It is expected that initially, some amount of human intervention may be required to execute experiments, but that the degree to which this is necessary will decline rapidly as the program progresses. Experimental platforms developed should be capable of executing experiments as directed and defined by the AI models (FA3), and in turn generate data of sufficient richness to inform and validate those models.

Performers are encouraged to build on existing experimental systems and expertise, and leverage existing equipment where possible to adhere to the aggressive program schedule as well as to mitigate overall system cost.

FA3: Representations, AI models, and optimization frameworks Performers will develop AI models and optimization frameworks that provide three capabilities:

property prediction, process optimization, and inverse molecular design. In achieving these capabilities, it is expected that these models will 1) utilize techniques such as active learning, reinforcement learning, adversarial networks, and Bayesian optimization in order to identify the most informative data to be acquired by FA1 tools or FA2 experimental platforms to further increase the accuracy of the models; and 2) incorporate contextual and physics-based information (e.g., molecular dynamics and others) in their representation of data. It is expected that while FA1

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and FA2 will be primary sources of such information, other means (e.g., simulation platforms or approximations thereof) will be utilized to augment and further enrich the data provided by FA1 and FA2. Proposals should fully describe the balance between experimental and virtual generation of data for AI models, and the scale and speed at which those data will be generated and integrated.

Approaches that allow for the simultaneous optimization of multiple objectives (i.e., properties or process parameters) are required.

Government teams interested in participating in IV&V should NOT respond to this BAA, but rather indicate their interest in the AMD program via email at AMD@darpa.mil for further details.

D. Program Structure AMD is a 48-month program divided into three Phases that are 14 month (Phase 1), 18 month (Phase 2) and 16 month (Phase 3) duration. Each phase will develop and enhance specific components of the overall system, as well as advance toward a fully integrated, autonomous closed-loop system by the end of the program. AMD performers will be expected to make specific, measurable progress in each Focus Area, however, the performance of the complete system and progress toward integration will be critically important.

Phase 1: Performers will adapt existing tools (e.g., NLP and CV) to chemistry data (focus on text and structure diagrams), develop hardware and control software for initial demonstrations of early-stage automated experimental systems, initiate transforms to extract data directly from proposed analytical instrumentation, and develop AI model architectures and active learning capabilities.

Phase 1 integration will focus on ensuring FA1 and FA2 data is amenable to the representations being developed in FA3. In parallel, performers will begin engaging with Government IV&V teams.

Phase 2: Performers will adapt and develop tools for extracting data from complex sources such as lab notebooks, tables and graphs, demonstrate automated experimentation informed by models and refine molecular representations. Phase 2 integration will focus on ensuring FA2 data is of value to FA3 models, and FA3-defined experiments can be executed on FA2 platforms with a human intermediary. Performers will begin transition of data, tools, and algorithms to Government IV&V teams, and begin initial application-specific testing and validation.

Phase 3: Performers will develop methods to accurately correlate data across multiple sources, demonstrate fully autonomous, closed-loop feedback between experimental platforms and AI models, and identify domains of greatest applicability for their developed models and representations. Phase 3 integration will focus on autonomous, closed-loop feedback between all Focus Areas without humans in the loop. Performers and Government IV&V teams will further refine approaches towards application areas of interest and continue testing and validation.

Proposals must address all program requirements, metrics, and milestones during the full 48-month program. Performance will be evaluated throughout the program with respect to progress towards meeting the milestones indicated in Figure 1 that correspond to performance expectations as defined in Table 1. Proposers are also required to propose specific metrics and milestones that are relevant to the properties that will be the focus of their efforts. Performers will be expected to work openly and regularly with Government IV&V teams. Dedicated collaboration time will be

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provided at program review meetings and performer-driven information exchange is expected.

Proposals must include a task to reflect information and capability exchange for validation and testing; the details of the work arrangement will be defined as the program proceeds.

Figure 1: AMD Program Schedule

E. Schedule/Milestones Progression between phases and overall program success will be determined by performance on the AMD metrics defined below, as well as performer-defined, quantitative metrics that pertain to the specific properties, tools, data, and experimental systems that are proposed. Evaluation toward program goals will include Government IV&V assessment of tools, data, models, and experimental systems for measuring, modeling, and predicting among a set of fundamental molecular properties toward specific applications.

Proposals must include specific quantitative metrics for each program phase. DARPA anticipates a range of aggressive metrics that are specific to the given properties being modeled and systems being developed, given the variability in state-of-the-art measurement and experimental tools, models, and data across the anticipated property space that will be explored in the program. Metrics must enable both evaluation of progress within each phase, and evidence toward overall closed-loop integration and automation that ultimately enables AI-based design of molecules with a defined set of properties. Proposals must benchmark metrics with comparison to existing technologies, data sets, and models.

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Details of AMD metrics and milestones are provided below in Table 1. Because these are dependent on existing tools, techniques, and methods for a given property or set of properties, performers must include justification for how these will be met and whether they can be surpassed.

As noted above, these are in addition to the performer-defined metrics that also must be included in the proposal.

Table 1: AMD Metrics

In addition to the metrics defined above, DARPA will issue various challenges (i.e., custom-designed system capabilities assessments) throughout the program for which performers will be provided with details on specific datasets, properties, or experiments on which their systems will be evaluated. These challenges will occur in months 22, 32, and 42. Throughout the program, DARPA will assess the diversity of small molecule space that is addressed, both experimentally and computationally using measures such as the Tanimoto coefficient.

The following additional criteria should be included/considered in proposals:

Proposers should provide a technical and programmatic strategy that conforms to the entire program schedule and presents an aggressive plan to fully address all program goals, metrics, milestones, and deliverables.

The task structure must be consistent across the proposed schedule, Statement of Work, and cost volume.

A target start date of July 2019 may be assumed for planning purposes.

Schedules will be synchronized across performers, as required, and monitored/revised as necessary, throughout the program.

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All proposals must include the following meetings and travel in the proposed schedule and costs:

o To foster collaboration between teams, and disseminate program developments, a two-day Principal Investigator (PI) meeting will be held approximately every six months in the Washington, DC area. For budgeting purposes, plan for eight (8) two-day meetings over the course of 48 months.

o Regular teleconference meetings will be scheduled with the Government team for progress reporting as well as problem identification and mitigation.

Proposers should also anticipate at least one site visit per phase by the DARPA Program Manager during which they will have the opportunity to demonstrate progress towards agreed-upon milestones.

F. Deliverables Performers will be expected to provide at a minimum the following deliverables:

Comprehensive quarterly technical reports due within ten (10) calendar days of the end of the given quarter, describing progress made on the specific milestones as laid out in the Statement of Work (SOW).

A phase completion report submitted within 30 calendar days of the end of each phase, summarizing the research done.

Deliverables including, but not limited to data, models, tools, and experimental capabilities developed as part of the program will be transitioned to Government IV&V teams as requested.

Other negotiated deliverables specific to the objectives of the individual efforts. These may include registered reports, experimental protocols, publications, data management plan, intermediate, and final versions of software libraries, code, and APIs, including documentation and user manuals, and/or a comprehensive assemblage of design documents, models, modeling data and results, and model validation data.

Reporting as outlined in Section VI.C.

G. Government-furnished Property/Equipment/Information None

H. Other Program Objectives and Considerations

1. Collaboration

DARPA expects all performers to work collaboratively with Government IV&V teams to realize the program objectives outlined herein. Proposers should carefully review the goals for the entire program in order to fully understand the context of each program objective within the overall program structure. Furthermore, throughout development of program technologies, it will be necessary for all performers to share relevant information regarding their technology development to support the larger program goals. For example, Government IV&V teams will need access to the datasets, models, tools, and experimental systems developed by AMD performers. All proposals must clearly describe plans for interfacing and integrating their proposed technologies/approaches with other performers. Proposals that fail to include interface and integration plans will be deemed non-conforming and removed from consideration for award.

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2. Intellectual Property As discussed above, there is an emphasis on creating and leveraging open source technologies and architectures, making data sharing and collaboration key aspects of this program. Therefore, intellectual property rights asserted by proposers are strongly encouraged to be aligned with open source regimes. See Section VI.B.4 for more information related to intellectual property.

II. Award Information

A. General Award Information DARPA anticipates multiple awards.

The level of funding for individual awards made under this BAA will depend on the quality of the proposals received and the availability of funds. Awards will be made to proposers1 whose proposals are determined to be the most advantageous to the Government, all evaluation factors considered. See Section V for further information.

The Government reserves the right to:

select for negotiation all, some, one, or none of the proposals received in response to this solicitation;

make awards without discussions with proposers;

conduct discussions with proposers if it is later determined to be necessary;

segregate portions of resulting awards into pre-priced options;

accept proposals in their entirety or to select only portions of proposals for award;

fund awards in increments with options for continued work at the end of one or more phases;

request additional documentation once the award instrument has been determined (e.g., representations and certifications); and remove proposers from award consideration should the parties fail to reach agreement on award terms within a reasonable time or the proposer fails to provide requested additional information in a timely manner.

Proposals identified for negotiation may result in a procurement contract, grant, cooperative agreement, or other transaction (OT), depending upon the nature of the work proposed, the required degree of interaction between parties, and other factors.

1 As used throughout this BAA, “proposer” refers to the lead organization on a submission to this BAA. The proposer is responsible for ensuring that all information required by a BAA--from all team members--is submitted in accordance with the BAA. “Awardee” refers to anyone who might receive a prime award from the Government, including recipients of procurement contracts, grants, cooperative agreements, or Other Transactions. “Sub awardee” refers to anyone who might receive a sub award from a prime awardee (e.g., sub awardee, consultant, etc.).

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Proposers looking for innovative, commercial-like contractual arrangements are encouraged to consider requesting Other Transactions. To understand the flexibility and options associated with Other Transactions, consult http://www.darpa.mil/work-with-us/contract-management#OtherTransactions.

In accordance with 10 U.S.C. § 2371b(f), the Government may award a follow-on production contract or Other Transaction (OT) for any OT awarded under this BAA if: (1) that participant in the OT, or a recognized successor in interest to the OT, successfully completed the entire prototype project provided for in the OT, as modified; and (2) the OT provides for the award of a follow-on production contract or OT to the participant, or a recognized successor in interest to the OT.

In all cases, the Government contracting officer shall have sole discretion to select award instrument type, regardless of instrument type proposed, and to negotiate all instrument terms and conditions with selectees. DARPA will apply publication or other restrictions, as necessary, if it determines that the research resulting from the proposed effort will present a high likelihood of disclosing performance characteristics of military systems or manufacturing technologies that are unique and critical to defense. Any award resulting from such a determination will include a requirement for DARPA permission before publishing any information or results on the program. For more information on publication restrictions, see the section below on Fundamental Research.

B. Fundamental Research

It is DoD policy that the publication of products of fundamental research will remain unrestricted to the maximum extent possible. National Security Decision Directive (NSDD) 189 defines fundamental research as follows:

‘Fundamental research’ means basic and applied research in science and engineering, the results of which ordinarily are published and shared broadly within the scientific community, as distinguished from proprietary research and from industrial development, design, production, and product utilization, the results of which ordinarily are restricted for proprietary or national security reasons.

As of the date of publication of this BAA, the Government expects that program goals as described herein may be met by proposers intending to perform fundamental research and does not anticipate applying publication restrictions of any kind to individual awards for fundamental research that may result from this BAA. Notwithstanding this statement of expectation, the Government is not prohibited from considering and selecting research proposals that, while perhaps not qualifying as fundamental research under the foregoing definition, still meet the BAA criteria for submissions. If proposals are selected for award that offer other than a fundamental research solution, the Government will either work with the proposer to modify the proposed statement of work to bring the research back into line with fundamental research or else the proposer will agree to restrictions in order to receive an award.

Proposers should indicate in their proposal whether they believe the scope of the research included in their proposal is fundamental or not. While proposers should clearly explain the intended results of their research, the Government shall have sole discretion to determine http://www.darpa.mil/work-with-us/contract-management#OtherTransactions http://www.darpa.mil/work-with-us/contract-management#OtherTransactions

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whether the proposed research shall be considered fundamental. Appropriate clauses will be included in resultant awards for non-fundamental research to prescribe publication requirements and other restrictions, as appropriate. This clause can be found at www.darpa.mil/work-with-us/additional-baa.

For certain research projects, it may be possible that although the research to be performed by a potential awardee is restricted research, their sub awardee’s effort may be fundamental research.

In those cases, it is the awardee’s responsibility to explain in their proposal why its sub awardee’s effort is fundamental research.

Proposers should indicate in their proposal whether they believe the scope of the research included in their proposal is fundamental or not. While proposers should clearly explain the intended results of their research, the Government shall have sole discretion to determine whether the proposed research shall be considered fundamental. Appropriate clauses will be included in resultant awards for non-fundamental research to prescribe publication requirements and other restrictions, as appropriate. This clause can be found at www.darpa.mil/work-with-us/additional-baa.

For certain research projects, it may be possible that although the research to be performed by a potential awardee is restricted research, their subawardee’s effort may be fundamental research.

In those cases, it is the awardee’s responsibility to explain in their proposal why its subawardee’s effort is fundamental research.

III. Eligibility Information A. Eligible Applicants

All responsible sources capable of satisfying the Government's needs may submit a proposal for DARPA’s consideration.

1. Federally Funded Research and Development Centers (FFRDCs) and Government Entities

a. FFRDCs

FFRDCs are subject to applicable direct competition limitations and cannot propose to this BAA in any capacity unless they meet the following conditions: (1) FFRDCs must clearly demonstrate that the proposed work is not otherwise available from the private sector. (2) FFRDCs must provide a letter on official letterhead from their sponsoring organization citing the specific authority establishing their eligibility to propose to Government solicitations and compete with industry, and their compliance with the associated FFRDC sponsor agreement’s terms and conditions. This information is required for FFRDCs proposing to be awardees or subawardees.

b. Government Entities http://www.darpa.mil/work-with-us/additional-baa http://www.darpa.mil/work-with-us/additional-baa http://www.darpa.mil/work-with-us/additional-baa

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Government entities (e.g., Government/National laboratories, military educational institutions, etc.) are subject to applicable direct competition limitations. Government entities must clearly demonstrate that the work is not otherwise available from the private sector and provide written documentation citing the specific statutory authority and contractual authority, if relevant, establishing their ability to propose to Government solicitations. This information is required for Government entities proposing to be awardees or subawardees.

c. Authority and Eligibility

At the present time, DARPA does not consider 15 U.S.C. § 3710a to be sufficient legal authority to show eligibility. While 10 U.S.C.§ 2539b may be the appropriate statutory starting point for some entities, specific supporting regulatory guidance, together with evidence of agency approval, will still be required to fully establish eligibility. DARPA will consider FFRDC and Government entity eligibility submissions on a case-by-case basis; however, the burden to prove eligibility for all team members rests solely with the proposer.

2. Foreign Participation Non-U.S. organizations and/or individuals may participate to the extent that such participants comply with any necessary nondisclosure agreements, security regulations, export control laws, and other governing statutes applicable under the circumstances. For classified submissions, this includes mitigating any Foreign Ownership Control and Influence (FOCI) issues prior to transmitting the submission to DARPA. Additional information on these subjects can be found at http://www.dss.mil/isp/foci/foci_faqs.html.

B. Organizational Conflicts of Interest

FAR 9.5 Requirements In accordance with FAR 9.5, proposers are required to identify and disclose all facts relevant to potential OCIs involving the proposer’s organization and any proposed team member (subawardee, consultant). Under this Section, the proposer is responsible for providing this disclosure with each proposal submitted to the BAA. The disclosure must include the proposer’s, and as applicable, proposed team member’s OCI mitigation plan. The OCI mitigation plan must include a description of the actions the proposer has taken, or intends to take, to prevent the existence of conflicting roles that might bias the proposer’s judgment and to prevent the proposer from having unfair competitive advantage. The OCI mitigation plan will specifically discuss the disclosed OCI in the context of each of the OCI limitations outlined in FAR 9.505-1 through FAR 9.505-4.

Agency Supplemental OCI Policy In addition, DARPA has a supplemental OCI policy that prohibits contractors/performers from concurrently providing Scientific Engineering Technical Assistance (SETA), Advisory and Assistance Services (A&AS) or similar support services and being a technical performer.

Therefore, as part of the FAR 9.5 disclosure requirement above, a proposer must affirm whether the proposer or any proposed team member (subawardee, consultant) is providing SETA, A&AS, http://www.dss.mil/isp/foci/foci_faqs.html

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or similar support to any DARPA office(s) under: (a) a current award or subaward; or (b) a past award or subaward that ended within one calendar year prior to the proposal’s submission date.

If SETA, A&AS, or similar support is being or was provided to any DARPA office(s), the proposal must include:

The name of the DARPA office receiving the support;

The prime contract number;

Identification of proposed team member (subawardee, consultant) providing the support; and An OCI mitigation plan in accordance with FAR 9.5.

Government Procedures In accordance with FAR 9.503, 9.504 and 9.506, the Government will evaluate OCI mitigation plans to avoid, neutralize or mitigate potential OCI issues before award and to determine whether it is in the Government’s interest to grant a waiver. The Government will only evaluate OCI mitigation plans for proposals that are determined selectable under the BAA evaluation criteria and funding availability.

The Government may require proposers to provide additional information to assist the Government in evaluating the proposer’s OCI mitigation plan.

If the Government determines that a proposer failed to fully disclose an OCI; or failed to provide the affirmation of DARPA support as described above; or failed to reasonably provide additional information requested by the Government to assist in evaluating the proposer’s OCI mitigation plan, the Government may reject the proposal and withdraw it from consideration for award.

C. Cost Sharing/Matching Cost sharing is not required; however, it will be carefully considered where there is an applicable statutory condition relating to the selected funding instrument (e.g., OTs under the authority of 10 U.S.C. § 2371).

For more information on potential cost sharing requirements for Other Transactions for Prototype, see http://www.darpa.mil/work-with-us/contract-management#OtherTransactions.

IV. Application and Submission Information Prior to submitting a full proposal, proposers are strongly encouraged to first submit an abstract as described below. This process allows a proposer to ascertain whether the proposed concept is: (1) applicable to the AMD BAA and (2) currently of interest. For the purposes of this BAA, applicability is defined as follows:

The proposed concept is applicable to the technical areas described herein.

The proposed concept investigates an innovative approach that enables revolutionary advances, i.e., will not primarily result in evolutionary improvements to the existing state of practice.

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The proposed work has not already been completed (i.e., the research element is complete but manufacturing/fabrication funds are required).

The proposer has not already received funding or a positive funding decision for the proposed concept (whether from DARPA or another Government agency).

Abstracts and full proposals that are not found to be applicable to the Accelerated Molecular Discovery BAA as defined above may be deemed non-conforming2 and removed from consideration. All abstracts and full proposals must provide sufficient information to assess the validity/feasibility of their claims as well as comply with the requirements outlined herein for submission formatting, content and transmission to DARPA. Abstracts and full proposals that fail to do so may be deemed non-conforming and removed from consideration. Proposers will be notified of non-conforming determinations via letter.

A. Address to Request Application Package This document contains all information required to submit a response to this solicitation. No additional forms, kits, or other materials are needed except as referenced herein. No request for proposal or additional solicitation regarding this opportunity will be issued, nor is additional information available except as provided at the Federal Business Opportunities website (http://www.fbo.gov), the Grants.gov website (http://www.grants.gov/), or referenced herein.

B. Content and Form of Application Submission

1. Abstract Information

As stated above, proposers are strongly encouraged to submit an abstract in advance of a full proposal to minimize effort and reduce the potential expense of preparing an out of scope proposal. The abstract provides a synopsis of the proposed project by briefly answering the following questions:

What is the proposed work attempting to accomplish or do?

How is it done today, and what are the limitations?

Who will care and what will the impact be if the work is successful?

How much will it cost, and how long will it take?

DARPA will respond to abstracts with a statement as to whether DARPA is interested in the idea. If DARPA does not recommend the proposer submit a full proposal, DARPA will provide feedback to the proposer regarding the rationale for this decision. Regardless of DARPA’s response to an abstract, proposers may submit a full proposal. DARPA will review all conforming full proposals using the published evaluation criteria and without regard to any comments resulting from the review of an abstract. Proposers should note that a favorable response to an abstract is not a guarantee that a proposal based on the abstract will ultimately be selected for award negotiation.

2 “Conforming” is defined as having been submitted in accordance with the requirements outlined herein.

http://www.fbo.gov/ http://www.grants.gov/

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While it is DARPA policy to attempt to reply to abstracts within 30 calendar days, proposers to this solicitation may anticipate a response within approximately three weeks. These official notifications will be sent via email to the Technical POC and/or Administrative POC identified on the abstract coversheet.

a. Abstract Format All proposers are required to use Attachment A: Abstract Summary Slide Template and Attachment B: Abstract Template provided to this solicitation on http://www.fbo.gov and http://www.grants.gov. Attachment A Abstract Summary Slide Template described herein must be in .ppt or .pptx format and should be attached as a separate file to this document.

2. Full Proposal Information Proposals consist of Volume 1: Technical and Management Volume, Volume 2: Cost Volume, and Volume 3: Administrative and National Policy Requirements).

To assist in proposal development, various attachments have been provided along with the BAA posted on http://www.fbo.gov (Attachment C: Proposal Summary Slide Template, Attachment D: Proposal Template Volume 1 Technical & Management Volume, Attachment E: Proposal Template Volume 2 Cost Volume, Attachment F: Cost Summary Spreadsheet, Attachment F-2:

Proposal Template Volume 2 Cost Breakdown Template, and Attachment G: Proposal…