[Federal Register Volume 70, Number 250 (Friday, December 30, 2005)]
[Notices]
[Pages 77419-77420]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: E5-8133]


-----------------------------------------------------------------------

DEPARTMENT OF HEALTH AND HUMAN SERVICES

National Institutes of Health


Prospective Grant of Exclusive License: Software for Predicting 
Molecular Properties and Pathogen Detection

AGENCY: National Institutes of Health, Public Health Service, HHS.

ACTION: Notice.

-----------------------------------------------------------------------

SUMMARY: This is notice, in accordance with 35 U.S.C. 209(c)(1) and 37 
CFR 404.7(a)(1)(i), that the National Institutes of Health (NIH), 
Department of Health and Human Services, is contemplating the grant of 
an exclusive worldwide license to practice the invention embodied in E-
169-2000/0 ``Drift Compensation Method for Fingerprint Spectra,'' U.S. 
Patent Application No. 09/975,530 filed October 10, 2001; E-297-2001/0 
``Methods For Predicting Properties of Molecules,'' U.S. Patent 
Application No. 10/383,602 filed March 7, 2003; and E-017-2003/0 
``Improved Pattern Recognition Of Whole Cell Mass Spectra Via 
Separation Of Specific Charge States,'' U.S. Patent Application No. 10/
863,745 filed June 7, 2004; to Litmus, LLC an Arkansas corporation 
having its headquarters in Little Rock, Arkansas. The United States of 
America is the assignee of the patent rights of the above inventions.
    The contemplated exclusive license may be granted in the field of 
providing software solutions for pathogen detection and for predicting 
molecular properties.

DATES: Only written comments and/or applications for a license received 
by the NIH Office of Technology Transfer on or before February 28, 2006 
will be considered.

ADDRESSES: Requests for a copy of the patent applications, inquiries, 
comments and other materials relating to the contemplated license 
should be directed to: Michael A. Shmilovich, Esq., Office of 
Technology Transfer, National Institutes of Health, 6011 Executive 
Boulevard, Suite 325, Rockville, MD 20852-3804; Telephone: (301) 435-
5019; Facsimile: (301) 402-0220; E-mail: [email protected]. A 
signed confidentiality nondisclosure agreement may be required to 
receive copies of the patent applications.

SUPPLEMENTARY INFORMATION: The patent applications intended for 
licensure disclose and/or cover the following:

E-297-2001 ``Methods For Predicting Properties of Molecules'' 
Quantitative Spectral data-activity relationships (QSDAR)

    The invention relates to methods for predicting the biological, 
chemical, and physical properties of molecules from their chemical 
shift through bond and through spatial distance connectivity patterns. 
This invention is related to E-209-1999 (related to the SDAR patent 
that could use chemical shift through bond correlated data); however, 
here predicted NMR chemical shift data is used that has already been 
structurally assigned. The invention uses the carbon or other 
heteronuclear molecular skeleton atom to atom connectivity of the 
molecule instead of proton to proton or proton to carbon connectivity 
that can be obtained from NMR experimental spectra of unlabeled 
molecules. This allows a model to be built using a complete molecular 
connectivity pattern instead of a pattern developed from a set of 
individual 2 or 3 atom pieces of a molecule. A 2D through bond 
connectivity spectrum is produced with a cross peak bin ``hit'' 
occurring when there is an atom to atom bond connection. Only half of 
the spectrum is used because the spectrum is symmetrical. A 2D through 
space connectivity spectrum is simulated is produced with a cross peak 
bin ``hit'' occurring when there is a atom to atom distance r is within 
a certain specified range.
    The through bond and through space spectra can be reduced to 
principal components. The biological, chemical, and physical endpoints 
are added to the connectivity patterns and multiple linear regression 
(OVILS) or artificial neural networks (ANN) methods are applied to 
produce and validate the model. This provides a very rapid, reliable 
ability to model many different compounds. The model uses the 
structurally assigned chemical shifts from predicted NMR spectra. The 
through bond and through space connectivity patterns uses the 
structural assignment of the chemical shifts. The through bond 
connectivity pattern gives a local description of the atoms and the 
through space connectivity pattern gives a non-local description of the 
atoms. The combination of the through bond and through space molecular 
connectivity pattern provides a very precise pattern that can be used 
by pattern recognition software to produce a model. All parts of this 
model can be completely computerized. The ideas used in this model may 
be able to produce the highest cross-validated models of ``endpoints'' 
that are important to the public health service.

E-169-2000 ``Microbial Identification Databases''

    The invention is a method for, based on an assembled coherent 
database, containing an essentially unlimited number of pyrolysis mass 
spectra to enable rapid chemotaxonomy of unknown microbial samples. The 
invention corrects for short- and long-term drift of microbial 
pyrolysis mass spectra by using spectra of similar microbes as internal 
standards. The invention provides a way to assemble a coherent database 
containing an essentially unlimited number of pyrolysis mass spectra or 
other instrumental ``fingerprints,'' where one or more is 
representative of each relevant strain, and representative of 
additional strains as they are added to the pool of microbial agents. 
Microorganisms can be identified using the invention from their 
fingerprint spectra regardless of the growth medium used to culture the 
bacteria. This is a result of the discovery that corrections made to 
the fingerprint spectrum of one type of bacterium to compensate for 
changes in growth medium may be applied successfully to metabolically 
similar bacteria. Fingerprint spectra to which the method of the 
invention may be applied include pyrolysis MALDI or other types of mass 
spectra, infrared spectra, chromatograms, NMR spectra and ion-mobility 
spectra. The present invention is especially useful for the rapid 
identification of microorganisms, including human pathogens.

[[Page 77420]]

E-017-2003 ``Pattern Recognition of Whole Cell Mass Spectra''

    This invention analyzes mass spectra (MALDI, SELDI) from a 
plurality of microorganism sources and biological agents. The invention 
is useful for diagnosing disease, anticipating epidemic outbreaks, 
monitoring food supplies for contamination, regulating bio-processing 
operations, and is especially useful for detecting agents of war. The 
invention dramatically improves spectral analysis through deconvolution 
of complex spectra by collapsing multiple peaks showing different 
molecular mass originating from the same molecular fragment into a 
single peak. The differences in molecular mass are apparent differences 
caused by different charge states of the fragment and/or different 
metal ion adducts of one or more of the charge states. The deconvoluted 
spectrum is compared to a library of mass spectra acquired from samples 
of known identity to unambiguously determine the identity of one or 
more components of the sample undergoing analysis.
    The prospective exclusive license will be royalty bearing and will 
comply with the terms and conditions of 35 U.S.C. 209 and 37 CFR 404.7. 
The prospective exclusive license may be granted unless, within sixty 
(60) days from the date of this published notice, NIH receives written 
evidence and argument that establishes that the grant of the license 
would not be consistent with the requirements of 35 U.S.C. 209 and 37 
CFR 404.7.
    Properly filed competing applications for a license filed in 
response to this notice will be treated as objections to the 
contemplated license. Comments and objections submitted in response to 
this notice will not be made available for public inspection, and, to 
the extent permitted by law, will not be released under the Freedom of 
Information Act, 5 U.S.C. 552.

    Dated: December 14, 2005.
Steven M. Ferguson,
Director, Division of Technology Development and Transfer, Office of 
Technology Transfer, National Institutes of Health.
 [FR Doc. E5-8133 Filed 12-29-05; 8:45 am]
BILLING CODE 4140-01-P