**NSTC Research Business Models Comments**

October 4, 2003

Sarah Marston, PhD

1201 S Eads #1716

Arlington, VA 22202

Affiliations: (statistical software development, private sector,
pharmaceutical industry)

StatSci

Degge Group

smarston@pharmastatsci.com

Thank you for initiating a review of policies and procedures directed
towards improving the performance and management of federally funded
science and engineering research. Please find my comments and
suggestions below.

# **Summary of Concerns**

It isn't a good idea to invest in R&D without assessing the
effectiveness and net impact of that investment; conceivably, the
current federally funded R&D programs deliver a net negative as opposed
to a net positive impact. The specific areas of concerns are listed
below followed by suggestions.

1)  Excessive Overhead at the NIH.

2)  Absence of Basic Performance Assessments.

3)  Absence of Balance Across Disciplines in R&D Funding.

4)  Disruptions of the S&E Workforce Due to Graduate Student-Postdoc
    Issues.

## 

## Accountability

# "Analyzable" Funding Database

Before we can evaluate the performance and assess the overall impact, we
need to know how the tax dollars are invested. To that end, as a first
step towards improving accountability, I suggest development of an
"analyzable" publically accessible funding database. The content could
include key parameters of interest such as type of research (ie early
stage, applied), type of study (ie laboratory, clinical), goal (ie
advance knowledge of \<whatever\>, assess efficacy of treatment x vs y,
etc), justification (explanation for why this research is funded, the
pay-off), deliverable (ie knowledge, new technology, new treatment),
outcome metric (ie the measure of performance), and outcome (success or
failure). In addition, higher order parameters such as classification by
disease, technology, or basic knowledge, etc could be available for the
purpose of macro and program level summarization. Information on
overhead costs, including extramural contracts, also needs to be
available. In the end, it should be possible to conveniently assess
progress towards meeting program level goals. The identification and
classification of key parameters is best done by independent,
non-government agency, third party resources, including professionals
with diverse backgrounds (industry R&D, business management, etc) from
the general population. It is of critical importance to involve the
tax-paying public and potential consumers of the research.

# Research on Research Program

In addition to a database, the federal government can provide support
for a comprehensive research on research program by taking a proportion
of the funding available to the funding agencies. Research on research
initiatives could include development of R&D performance metrics,
reviews of funding performance and process, etc. A monthly electronic
funding newsletter reporting on the awards and the results associated
with previously funded research can be supported. It is especially
important to provide mechanisms and incentives for inviting
participation from diverse groups.

# Competition

Introducing transparency and inviting comments from an inclusive and
diverse group can substantially increase performance and accountability,
but introducing competition can potentially drive the funding towards
even higher levels of effectiveness. This was evident with the
sequencing of the human genome project, the government funded program
came in early and on budget due to competition from the private sector
company, Celera. Competition can be introduced by decentralizing the
funding decision process, perhaps by shifting the dollars back to the
states. Alternatively, establishing a competitive environment across
federal agencies, associated with break-up of the NIH into smaller, more
focused research centers could represent another mechanism for
introducing competition.

# Basic-Applied Research Models

With respect to software development, a number of successful non-profit
open source -- commercial spin-off models have been established. This
concept can be expanded to establish "communities" focused on tackling
challenging applications. This type of structure can facilitate driving
at least some of the R&D towards solving problems the private sector
can't address independently due to high R&D costs or small market size.
This type of initiative contributes to the issue of accountability by
providing a more direct, visible pay-off to the public.

To summarize, this level of transparency and ease-of-access to data
provides opportunities for a broader range of feedback and peer review,
a key component in improving performance. In addition, it provides a
mechanism to more adequately inform the public.

## Research Support

The current system, allocation of research dollars essentially via one
agency (the NIH), clearly stifles innovation. This relatively homogenous
group tends to jump on one "hot" area and funds that to the exclusion of
anything else. Further, due to the lack of balance in the allocation of
federal dollars, competent professionals in other fields tend to be
displaced and leave research entirely. Finally, the workforce policies
and practices, particularly with respect to the graduate and post-doc
opportunities, drive talented professionals towards other careers
leading to a well-established "brain drain" phenomenon. The suggestions
submitted with reference to accountability are applicable with respect
to research support. Transparency, performance, and accountability, with
a focus on meeting clearly stated goals, are key to promoting
innovation. For the short run, it is particularly important to address
the NIH post-doc issues, the dumping of thousands of PhDs disrupts the
market, ultimately suffocating innovation by via creating conditions of
severe overcapacity.

## Multidisciplinary/collaborative research

Grants proposing this type of research are likely not written and
submitted due to a number of factors, 1) an expected low probability of
success in obtaining funding, 2) obstacles preventing many professionals
working at universities to find the time and opportunity to broaden the
scope of their research, and 3) a record of funding the same
professionals lacking the concept of a team approach (ie they have to be
the "big chief"). Multidisciplinary teams are the rule rather than the
exception in R&D intensive companies, and frequently large, well-funded
universities can support integration across disciplines. Providing
opportunities for industry R&D professionals to re-enter academic
research could perhaps facilitate increased collaborative research. But
the most substantial changes can come from restructuring the peer-review
process and broadening the pool of applicants by increasing the
probability of obtaining funding for new investigators with new ideas.

## Information Technology

The NIH could streamline the submission-funding process and also
facilitate execution of clinical trials via effective application of
information technology. Pharmaceutical industry already relies on
document management and clinical trial software applications to
streamline processing, the NIH has failed to successfully contract and
install these types of applications. Review of the NIH overhead and
establishment of performance metrics can encourage the NIH to move more
aggressively towards delivering successful IT solutions to reduce
overhead.