Chemistry: molecular biology and microbiology – Measuring or testing process involving enzymes or... – Involving viable micro-organism
Reexamination Certificate
2001-10-30
2003-06-03
Leary, Louise N. (Department: 1627)
Chemistry: molecular biology and microbiology
Measuring or testing process involving enzymes or...
Involving viable micro-organism
C435S004000, C435S030000, C435S288700, C435S032000, C435S968000
Reexamination Certificate
active
06573063
ABSTRACT:
FIELD OF THE INVENTION
The methods and system of the present invention employ optical, or spectroscopic, detection techniques for assessing the health physiological condition, and viability of biological materials such as tissues, cells, and subcellular components, and may be used in both in vitro and in vivo systems. One important application of the methods and apparatus of the present invention is high throughput screening of candidate agents and conditions to evaluate their suitability as diagnostic or therapeutic agents.
BACKGROUND OF THE INVENTION
Biology has undergone a change so fundamental that it has been compared to the industrial revolution of the 19
th
century and the advances in quantum physics in the 20
th
, century. The complete sequencing of the human genome and of the genomes of many microbes and plants has given rise to genomics, the discipline defined as the study of the structure and function of large number of genes undertaken in a simultaneous fashion. While the value of genomics as a basic tool for biological research has been clearly demonstrated, the impact on drug discovery remains unrealized. It is now clear that knowledge of gene sequences does not imply an understanding of their function. For example, inferred function based on the study of homologs from model organisms allows only the assignment of function to approximately 10% of the genes of mouse and humans. Clearly, the understanding of the function of genes at all organizational levels of biology will be the primary challenge of the post-genomics era.
The breadth and scale of the research efforts in genomics and related disciplines has resulted in the generation of large quantities of data that are difficult to examine or understand. Evolving relational databases will include not just primary biological data, but also predictions of protein structure, dynamic models of complex physiological processes, and the statistical treatment of data. The evolution of bioinformatics has occurred in parallel with the creation of increasingly sophisticated tools for compiling and analyzing chemical data. Theoretical and experimental chemical data is being incorporated into advanced chemical databases that are being relationally connected to genomic databases to give rise to the field of chemical genomics. Finally, engineering and the physical sciences play a crucial role in the post-genomics era. Advances in analytical chemistry, analytical biochemistry, image analysis, robotics and process automation have enabled the task of developing advanced biological databases.
In spite of the availability of numerous targets for drug discovery, the overall success rate of the process remains abysmally low. At present, it is fair to say that the question How does one apply information about gene and gene products to the discovery of new drugs remains largely unanswered. There are three main reasons for low success rates in the conversion of vast amounts of genomics information to viable products: (1) lack of clear criteria for target validation; (2) hits to leads decisions based on potency and selectivity against molecular targets, with limited physiological information; and (3) nonviable leads due to poor adsorption, undesirable metabolism, toxicity, or unacceptable side effects.
Drug development programs rely on in vitro screening assays and subsequent testing in appropriate animal models to evaluate drug candidates prior to conducting clinical trials using human subjects. Screening methods currently used are generally difficult to scale up to provide the high throughput screening necessary to test the numerous candidate compounds generated by traditional and computational means. Moreover, studies involving cell culture systems and animal model responses frequently don't accurately predict the responses and side effects observed during human clinical trials.
Conventional methods for assessing the effects of various agents or physiological activities on biological materials, in both in vitro and in vivo systems, generally are not highly sensitive or informative. For example, assessment of the effect of a physiological agent, such as a drug, on a population of cells or tissue grown in culture, conventionally provides information relating to the effect of the agent on the cell or tissue population only at specified points in time. Additionally, current assessment techniques generally provide information relating to a single or a small number of parameters. Candidate agents are systematically tested for cytotoxicity, which may be determined as a function of concentration. A population of cells is treated and, at one or several time points following treatment, cell survival is measured. Cytotoxicity assays generally do not provide any information relating to the cause(s) or time course of cell death.
Similarly, agents are frequently evaluated based on their physiological effects, for example, on a particular metabolic function or metabolite. An agent is administered to a population of cells or a tissue sample, and the metabolic function or metabolite of interest is assayed to assess the effect of the agent. This type of assay provides useful information, but it does not provide information relating to the mechanism of action, the effect on other metabolites or metabolic functions, the time course of the physiological effect, general cell or tissue health, or the like.
Optical techniques have been developed and used for several applications. Light scattering has been used in the past to provide measurements of osmotic water permeability in suspensions of osmotically responsive vesicles and small cells. A. S. Verkman, “Optical Methods to Measure Membrane Transport Processes,”
J. Membrane Biol
. 148:99-110, 1995. Another study reported a method for the optical measurement of osmotic water transport in cultured cells. M. Echevarria, A. S. Verkman, “Optical Measurement of Osmotic Water Transport in Cultured Cells: Role of Glucose Transporters,”
J. Gen. Physiol
. 99:573-589, 1992.
Optical techniques for observing nerve activity and neuronal tissue are well-established. Hill and Keynes observed that the nerve from the walking leg of the shore crab normally has a whitish opacity caused by light scattering, and that opacity changes evoked by electrical stimulation of that nerve were measurable. Hill, D. K. and Keynes, R. D., “Opacity Changes in Stimulated Nerve,”
J. Physiol
. 108:278-281, 1949. Since the publication of those results, experiments designed to learn more about the physiological mechanisms underlying the correlation between optical and electrical properties of neuronal tissue and to develop improved techniques for detecting and recording activity-evoked optical changes have been ongoing.
Intrinsic changes in optical properties of cortical tissue have been assessed by reflection measurements of tissue in response to electrical or metabolic activity. Grinvald, A., et al., “Functional Architecture of Cortex Revealed by Optical Imaging of Intrinsic Signals,”
Nature
324:361-364, 1986; Grinvald, et al., “Optical Imaging of Neuronal Activity, Physiological Reviews, Vol. 68, No. 4, October 1988. Grinvald and his colleagues reported that some slow signals from hippocampal slices could be imaged using a CCD camera without signal averaging.
A CCD camera was used to detect intrinsic signals in a monkey model. Ts'o, D. Y., et al., “Functional Organization of Primate Visual Cortex Revealed by High Resolution Optical Imaging,”
Science
249:417-420, 1990. The technique employed by Ts'o et al. would not be practical for human clinical use, since imaging of intrinsic signals was achieved by implanting a stainless steel optical chamber in the skull of a monkey and contacting the cortical tissue with an optical oil. Furthermore, in order to achieve sufficient signal to noise ratios, Ts'o, et al., had to average images over periods of time greater than 30 minutes per image.
The mechanisms responsible for intrinsic signals are not well understood. Possible sources of intrinsic signals include dilation of small
Cytoscan Sciences LLC
Leary Louise N.
Sleath Janet
Speckman Ann W.
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