Title of proposed idea: Disruptive Proteomics Technologies: Comprehensive Protein Identification in Clinical Samples

Nominator: NIH Institutes/Centers

Major obstacle/challenge to overcome:  Our ability to detect and quantify proteins in complex (e.g., clinical) samples is progressing steadily, but it is increasingly clear that order-of-magnitude improvements in the associated technologies would enable very significant advances over a range of biomedical research areas.   In other word, the current state-of-the-art is good, but limiting.  A few of the specific limits are:

• Expensive technology/instrumentation
• Because of the above, labs have limited access, but demand is high
• Current technology is not capable of proteome-wide measurements

Although NIH does fund some technology development in this area, there are not programs specifically aimed at development of so-called “disruptive” technologies, i.e., those that could afford very rapid, very significant gains, similar to those that occurred in DNA sequencing technology.

Emerging scientific opportunity ripe for Common Fund investment: The history of technology development for genome sequencing teaches that successfully fostering very significant technological advances in basic methods and instrumentation requires a sustained effort, significant funds, encouragement of  diverse approaches, a tolerance for taking risks (moderated by ongoing evaluation across the portfolio) and very focused, precisely articulated, assessable program goals. 

We propose an analogous technology development effort that aims to produce order-of-magnitude improvements in the detection, identification, and quantification of proteins in complex samples.  Moreover, the effort would explicitly emphasize an end-point relevant to clinical applications.

Several NIH institutes do fund technology development in this area. However, the program proposed here is justified as a Common Fund effort both because its benefits will cut across NIH (see below) and because it requires concerted management of all the grants under one program towards

 precise program goals (see below) to maximize the chances for success. Similarly, it is important that this proposed program not be combined with other technology development efforts.

Common Fund investment that could accelerate scientific progress in this field:  In a long-term technology development effort such as the one proposed here, it is difficult to anticipate what basic methodology holds the best potential for very significant improvement. The current dominant methodology for high-throughput detection and quantification of proteins is mass spectrometry (MS); it holds good potential for further incremental improvement, and it is possible that order-of-magnitude improvements could be stimulated by a well-targeted program. In addition, there are other technologies that hold promise for significant improvements, though they are currently less developed than MS, and not well-supported.  We therefore propose projects covering both MS and non-MS approaches.

Specific funding components proposed:

FOA  1: Technology Development: MS-based protein ID and quantitation .  (Years 1-5)

Goals include:

                                               i.     10-fold decrease in instrumentation cost (e.g., a $50,000 mass spectrometer)

                                             ii.     100-fold or 1000-fold increase in dynamic range

                                            iii.     10-fold increase in throughput

FOA 2:  Technology Development:  Non-MS-based protein ID and quantitation. )

Goals include:

i.      Develop protein ID/quant technologies that approach/exceed MS-based methods with respect to: accuracy, dynamic range, throughput, cost, and ability to analyze PTMs.

                                ii. Demonstrate orders-of-magnitude improvements with respect to dynamic range, throughput, cost.

FOAs 1 and 2 would need to justify their approaches relative to eventual advantages for translational or clinical use, for example:

- Improved discovery and/or assessment of biomarkers

- Rapid sample turn-around time

- Small input volume (1 mL of blood, etc.)

- Stored or banked samples, resilience to sample handling variability

- Analysis of clinically relevant sample sizes (100s to 1000’s), with no loss of specificity

For FOA’s 1 and 2 it is likely that a phased approach with milestones will be advantageous for incenting rapid development and managing risks. For example these FOA’s might encourage many applications and a high level of risk/reward with an initial three-year period, followed by an option to renew for a larger amount of funds contingent on reaching milestones. 

One issue not explicitly considered above is the development of computational tools for data analysis and integration for large protein datasets.  There are advantages in asking that this be integrated into the development of the technologies, and also the alternate approach of writing a separate FOA. Staff will need to research this issue.

If FOA’s 1 and 2 are successful, a follow-on FOA focusing on specific clinical applications would be considered.

Potential impact of Common Fund investment:  Orders-of-magnitude improvements in this area would enable very significant advances across the NIH portfolio. In basic research, it would enable the assessment of all proteins in a mixture; which in turn would enable, for example, more comprehensive assessment of gene expression, now largely inferred indirectly from RNA expression.  In discovery research, it would enable a more comprehensive assessment of the molecular consequences of variation (eg, an addition to GWAS, GTEx, large cohort studies); for translational research it is likely to afford many advantages for disease biomarker discovery and assessment. Finally, if all the goals are realized, there are clear ramifications for the clinic (patient sample testing, drug response/disease progression, etc.).

Title of proposed idea Centers for Research and Training in Quantitative and Systems Pharmacology

Nominator: NIH Institutes/Centers

Major obstacle/challenge to overcome: The focus of most of modern drug discovery has been on creating Ehrlich’s “magic bullet,” a drug that would hit only one target in the body effecting the desired change.  This model has been enormously helpful and led to many drug successes.  Yet even today, ninety percent of investigational drugs—i.e., those approved for trial—fail before being approved for use in patients. Many of these failures occur at the Phase II clinical trial level of development, making the failures very costly, and the majority fail for reasons of lack of efficacy.  Furthermore, all drugs have unintended effects as well as intended ones, and drugs show person to person variability in their effectiveness and toxicities.  Clearly, we can identify potential targets and make high affinity ligands for those, but we lack 1) a comprehensive knowledge of the role of these targets in human physiology and disease, 2) a quantitative and multi-scale understanding of how the targets modulate each other, and 3) how hitting more than one target sums to produce an observable phenotypic change.  Industry scientists confirm that these are major impediments for drug discovery and development in most therapeutic areas. 

We submit that there is a profound need to make a major shift in our approach to drug discovery and understanding drug action to fill in the context within which targets operate and how they produce their therapeutic action and side effects.  This proposal is not meant to encompass all of systems biology or pharmacology, but to add a more quantitative and integrative perspective to allow a systems level understanding of drug action.  Academic pharmacology, for the past thirty to forty years, has been largely focused on molecular pharmacology, providing an in depth understanding of individual molecular targets within the body.  There has also been a diminished level of academic research in clinical pharmacology, the discipline most aligned with understanding drug action.  There is now a timely and urgent need to stimulate Quantitative and Systems Pharmacology (QSP), an emerging discipline that proposes to build from an understanding of a drug's molecular interactions to an understanding of its temporal and dynamic modulation of cellular networks, impact on human pathophysiology, and optimal use in the clinic.  QSP builds upon classical and molecular pharmacology by adding omics approaches not available in earlier periods and recent modeling approaches that enable the deciphering of high volume data analysis.  It adds the horizontal integration and numerical quantitation of biological processes and mechanisms provided by systems biology and the vertical integration and statistical approaches characterized by PD/PK modeling and clinical pharmacology.  It is necessarily multi-disciplinary and highly integrative, operating across the biological hierarchy from biochemistry and cells to tissues and whole organs to animal studies and human patients.  Furthermore, for research to move rapidly in this emerging area, there must be a scientific workforce to drive it; currently, this is also an underserved need. 

Emerging scientific opportunity ripe for Common Fund investment: This recommendation arises from two workshops and a follow up white paper held at the NIH in 2008 and 2010 (http://meetings.nigms.nih.gov/?ID=8316) with participants from academia, industry and government.  The stimulus for the workshops was the lack of integration taking place between the pharmacology and the systems biology being supported by NIH and the need to address the poor success rate in drug discovery and development.  The workshops brought together researchers in pharmacology, systems biology, pharmacokinetics/pharmacodynamics, computer modeling and related areas with a focus on how systems biology was contributing to drug discovery and understanding of drug action now and in the future.  The major result of the first meeting was a strong recommendation to repeat the workshop.  The attendees recognized that they had something to offer each other, but felt they were currently far apart.  The second workshop focused on three different therapeutic areas with the idea that they could learn from each other’s successes and failures.  That QSP encompasses cells, organs, and virtually all therapeutic areas, with underlying principles to be discovered that span all these makes it highly appropriate for a Common Fund proposal.  The opportunity now exists to bring together researchers in these various areas in a common effort to expand our knowledge of drug action beyond drug target interactions to an understanding of how to use drugs alone or in combination to control biological systems that can produce shifts between disease and healthy phenotypes.

Common Fund investment that could accelerate scientific progress in this field:   The purpose of this Common Fund idea is to promote the use of QSP approaches for the study and elimination of a major roadblock in drug discovery and development, the complexity of drug targeting.  The centers mechanism is recommended to facilitate collaborative development of pioneering research, research training, and outreach programs in this emerging area and therefore stimulate the field as a whole. The focus of the centers should be the generation and testing of new ideas in QSP.  The primary justification for centers is the need for integration of research plus training, and integration across levels of biological organization, across scientific disciplines, and across therapeutic areas.  We believe that a community is emerging from the cognate disciplines that is highly motivated and ready for this effort to begin.  Initially, there will be limiting factors as outlined below in areas for exploration, but there exists the opportunity to package what exists and leverage it to greatly boost research in this area.  It is also suggested that the opportunity exists to employ industry academic partnerships to fully engage the expertise and creativity of industrial partners in idea generation and testing that will benefit all sectors.

Some of the immediate needs in QSP include the following areas thought to be ripe for exploration via collaborative/integrative centers: 1) the quantitative characterization of drug targets; 2) factors affecting patient response variability; 3) better animal and tissue models; 4) re-connection of medicinal chemistry and tissue pharmacology; 5) information exchange formats extending from chemistry to electronic medical records; 6) better computational models with pharmacological mechanisms; 7) development of systems approaches to failure analysis; 8) defining of core competencies for training in QSP; 9) development of pedagogical resources; 10) novel formats for training, including that for established investigators; and 11) novel academic industry partnerships covering research and training.

Potential impact of Common Fund investment:  The primary results of a successful QSP centers program are expected to include: 1) major advances in the fundamental understanding of how drugs act; 2) more direct translation of discoveries made in cells to patients; 3) improved biomarkers that assay directly the effects of drugs in tissues and patients; 4) a stronger scientific basis for multi-drug therapy and re-purposing of existing drugs and drug candidates abandoned in development; 5) a more rational basis for polypharmacy and predicting drug-drug interactions; 6) a higher success rate for new drug candidates successfully entering the market place with acceptable toxicities and predictive variability among patient types; 7) higher rates of success of clinical trials; and 8) a stronger investigator pool for academia and industry and a new generation of leaders in academic and industrial pharmacology.