Invented by Lance Gavin Laing, Brian Francis SULLIVAN, Celcuity Inc

The market for whole cell assays and methods has been experiencing significant growth in recent years. Whole cell assays are a crucial tool in drug discovery and development, allowing researchers to study the effects of compounds on living cells. These assays provide valuable insights into the efficacy, toxicity, and mechanism of action of potential drug candidates. The increasing prevalence of chronic diseases, such as cancer, cardiovascular disorders, and neurological conditions, has fueled the demand for new and effective therapeutics. Whole cell assays play a vital role in identifying and validating potential drug targets, as well as evaluating the safety and efficacy of drug candidates. This has led to a surge in the adoption of whole cell assays by pharmaceutical and biotechnology companies. One of the key drivers of the market for whole cell assays is the shift towards personalized medicine. With advancements in genomics and proteomics, there is a growing understanding that each patient’s response to a particular drug can vary significantly. Whole cell assays allow researchers to assess the drug response in a more holistic manner, taking into account the complex interactions within the cell. This enables the development of targeted therapies that are tailored to individual patients, leading to improved treatment outcomes. Another factor contributing to the growth of the market is the increasing focus on cell-based therapies. Stem cell research and regenerative medicine have gained significant attention in recent years, with the potential to revolutionize the treatment of various diseases. Whole cell assays are instrumental in characterizing and evaluating the functionality of stem cells, ensuring their safety and efficacy before clinical use. This has led to a surge in demand for whole cell assay methods that can accurately assess the therapeutic potential of stem cells. The market for whole cell assays and methods is also driven by technological advancements. The development of high-throughput screening platforms, automated imaging systems, and advanced data analysis tools has significantly enhanced the efficiency and accuracy of whole cell assays. These technological innovations have enabled researchers to screen large compound libraries, analyze complex cellular responses, and generate robust data for decision-making in drug discovery. However, the market for whole cell assays and methods is not without its challenges. The high cost associated with the development and implementation of these assays can be a barrier for smaller companies and academic institutions. Additionally, the complexity of whole cell assays requires specialized expertise and infrastructure, which may limit their widespread adoption. Despite these challenges, the market for whole cell assays and methods is projected to continue its growth trajectory. The increasing demand for personalized medicine, the rise of cell-based therapies, and ongoing technological advancements are expected to drive the market forward. As researchers continue to unravel the complexities of cellular processes and disease mechanisms, whole cell assays will remain a critical tool in the quest for novel therapeutics.

The Celcuity Inc invention works as follows

The disclosure provides methods to analyze disease cell response. In some embodiments, the method includes administering a therapeutic agent to disease cells from a subject using a device which measures at least a physiological parameter in a cell, determining if a change is observed in the physiologic parameters of the disease cells in response to the agent in comparison to a baseline or physiological parameter prior to administration of the agent, and then selecting the agent that causes the change. In embodiments the disease cells can be whole, viable and/or without labels.

Background for Whole Cell Assays and Methods

Since the discovery of chemicals and exogenous protein as effective human therapeutic agents for specific cellular targets, treatment of patients with disease has seen significant progress. There is much room for improvement when it comes to the treatment of common diseases like cancer. The Human Genome Project had as its main goal to identify the genetic causes of disease in order to improve the development of therapeutic interventions. According to reports, the Human Genome Project has identified all human genes. Statistics have shown that many of these genes are statistically associated with disease in human populations. But knowing the genetic link of a particular disease or detecting genetic biomarkers doesn’t always accurately predict the disease outcome or treatment. The genetic links, and even quantification of the protein expression levels from these genes have been very limited when it comes to determining the appropriate therapeutic course.

Petabytes of genetic data have been collected.” The genetic data has been analyzed using a large amount of computing power and statistical modeling. This process has revealed at least two important findings. A ‘disease’ is a first step. Breast cancer, for example, is heterogeneous, in part, because the genetic makeup of breast cancer can differ from that of another person, as well as protein expression levels and the response to treatment. “Second, the detection of genetic biomarkers is not predictive in most cases.

Contemporary drugs that are targeted to specific human cell models have been discovered and developed in a systematic way. These cell lines have been engineered in a way that allows for optimal screening of large libraries to find drugs with the desired activity against specific cellular targets. This process may be misleading in terms of the efficacy potential drugs, as clinical data indicates that every patient has a unique disease. Drug discovery and development processes are not very successful at identifying human responders prior to clinical trials. They also continue to have a high failure rates throughout the entire clinical development process. “Many of the drugs approved by the regulatory clinical process, which focuses on reducing the harm to patients, have poor efficacy in actual disease patient population.

Not all diseases that present to a clinical physician have the same origin. For example, the inflammation of bones joints can be caused by several factors, some internal and some external. Some are “genetically related” Some of the causes are unknown, while others have a genetic link. When the external pathogen is correctly identified, medical science can triage patients fairly effectively for infectious diseases. The tools available to physicians are limited when it comes to predicting which therapies will reduce inflammation caused by internal causes. Physicians do not know how the cells of a patient will react to the various therapeutics available for treating a disease that is clinically referred to as “inflammation”. They may be aware that a gene has been altered, but they do not understand how this will affect the course of a patient’s disease. They may know how a drug should act, but they may not understand why some patients are resistant or unresponsive to the drug’s activity.

Patients must be better able to identify the specific cause of their disease and make better-informed decisions for an effective treatment plan.” The human genome sequencing, along with other genetic quantification methods, has informed doctors that every patient’s illness is unique. This information has led to a new industry around personalized medicine. Each patient can receive a therapeutic regimen that is tailored for their specific disease. Specific gene-related diseases are the focus of drug development. The current toolset of prognostic analysis are not up to the task. “Genes may be present, but their function within the context of an individual is not correlated.

Companion diagnostics are a response to the fact that every patient is unique and that therapies often fail to produce a positive result. This diagnostic test uses biomarker detection to try and identify patients who are more likely than others to respond to certain drugs. The test looks for gene mutations, increased gene numbers, or altered gene expression levels. Most of these tests have success rates that are less than 50%.

There is a need for better prognostic markers for the effectiveness and safety of therapeutics in an individual.

Some drugs have been targeted at specific gene-related diseases.” This approach is not widely used due to the significant limitations of current prognostic toolset. The kits and methods described herein allow for the selection of a therapeutic agent which is effective against a particular disease. In some embodiments, a therapeutic agent is used to label whole free cells of diseased tissue within a CReMS. A change in a physiological parameter of these cells in the presence or absence of the agent can be detected. The subject is treated with a therapeutic agent that causes a change in the physiological parameter of the cell.

One aspect of the disclosure is methods for selecting one or more agents at the initial diagnostic stage or during treatment. In some embodiments, the method of selecting one or several therapeutic agents approved for use in treating a disease or disorders in an individual subject includes administering one of more therapeutic agents to one or more isolated disease cells from the subject using a cellular measurement system, and determining if a change is observed in the cellular parameter of the sample of disease cells in response to one or more agents in comparison to a baseline measurement before administration of one or more agents. The change in the cellular parameter indicates the agent’s therapeutic efficacy In some embodiments, the isolate disease cell sample is made up of label-free whole cells. In some embodiments, a change in the cellular parameter of the isolated disease cell over a predetermined period of time is continuously monitored. In some embodiments, the process further includes selecting the therapeutic agent (or combination of agents) that causes a change in at least one cellular or physiological parameter and then communicating this agent to the health care provider. In embodiments, administering a therapeutic agent or combination therapeutic agents to the subject that results in a change of at lease one cellular reaction or physiologic parameters is also included.

The method of selecting a treatment in an individual subject includes determining the therapeutic efficacy in an agent in an individual subject by administering it to at least one isolated cell from the subject, which is label-free, in a cellular reaction measurement system (CReMS). This cell can be selected from among cancer cells, cell samples from subjects with autoimmune diseases, cell samples from tissues infected with foreign agents, and combinations thereof.

The method of selecting a cancer treatment for an individual includes: determining the therapeutic efficacy for the cancer treatment in an individual by administering an agent to atleast one isolated cancer cell sample taken from the subject, in a biosensor. Continuously measuring the change in atleast one physiological response parameter for a predetermined period of time while the therapeutic agent is present. Selecting the therapeutic drug for the treatment of that subject who exhibits a difference in a physiological reaction parameter in comparison to a baseline measurement.

The disclosure also includes a kit that contains: a container containing a disease sample of an individual subject, and another container containing a control sample of an individual subject, as well as a biosensor, and computer executable instructions to convert data from the sensor into an output. This output will show a change over time in a cell physiological response parameter, which can be selected from a group of parameters including pH, cell adhesion and attachment patterns, cell proliferation, signaling and cell survival, density, size, shape, shape, cell, cell, cell, cell, cell, cell, cell, cell, cell, cell, cell, a cell, cell, a cell, cell, a cell, cell, cell, cell, cell, cell, cell, cell, cell, cell, cell, cell, cell, cell, cell, cell cell, cell, cell, cell, a cell, cell, cell, cell, cell, cell, cell, cell, cell, cell, polarity, polarity, cell, polarity, a cell’s size, and cell, a cell, the cell, the cell, the cell, the cell, the cell, the cell, the cell, the cell, the cell, the cell,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,

A. Definitions

All technical and scientific terms are used in this document with the same meaning that is understood by a person of ordinary knowledge. All publications, patents, published applications, and applications referred to in this document are incorporated herein by reference. In the event that a defined in this section conflicts with or is otherwise incompatible with a defined in the patents and applications, published applications, or other publications that have been incorporated in this section by reference, then the definition in this section will prevail. The following terms are used in this section with the following definitions.

The term “about” is used here to mean roughly, in the region of, or around. As used here, “about” means roughly, around, or in the vicinity. The term “about” is used to modify a numerical range by extending the boundaries above and below the numerical values. When the term?about? is used with a range of numerical values, it modifies the range by extending its boundaries above and below those numerical values. The term “about” is used in general to modify a numerical value by extending the boundaries above and below the numerical values stated. The term?about? is used to indicate a numerical difference of 10% between the stated value and a value that is above or below it. The term “about” can be interpreted in two ways. The term?about? means plus or minus 20 percent of the numerical value with which the number is used. About 50% is the range 45%-55%. The numerical ranges given here by endpoints encompass all fractions and numbers within the range. “1 to 5 includes 1, 1,5, 2, 2.75, 3, 3.90, 4, and 5)”.

The term “activator” is used to describe a person who activates a device. ?activate,? Or?perturb,? ?perturb,? ?perturbation? In relation to cells, the term “perturbation” refers to the subject or activity of physiologic manipulating a cell by using reagents or organic molecules or biochemicals or nucleic acid or proteins which have an effect well-known to those practicing in the art. The term “effect” refers to the modulation of cell physiologic activity, which may include but is not limited to up- or downregulation.

The term “assay” “The term ‘assay’ or assaying’ refers to an analysis that determines, for example, the presence, absence of kinetics and dynamics as well as quantity. “Assaying” is an analysis that determines the presence, absence or quantity of a target. It can also be used to determine its extent, kinetics or dynamics.

The term “attachment” is used to describe the attachment of a piece. “The terms?attach,? Refer to, for instance, a surface-modifying substance, a mobile, a ligand-candidate compound, and similar entities of the disclosure that are connected to a substrate, such as through physical absorption or chemical bonding. Particularly, ?cell attachment,? ?cell adhesion,? Cell adhesion,? “Cell attachment” refers to the binding or interaction of cells to a surface. For example, by culturing or interacting with cell anchoring materials or the like.

The term “attachment pattern” refers to observable traits or characteristics of a cell’s connection with a surface. The term “attachment pattern” refers to the observable traits and characteristics of a cell’s or cell sample?s connection with a surface. A pattern of attachment can be quantitative (e.g. number of sites). The pattern of attachment can be qualitative as well, for example, the preferred molecular site to attach to an extracellular matrix.

The term “antibody” is used in a broad sense and includes monoclonal antibodies (including full length monoclonal antibodies), humanized antibodies, chimeric antigens, multispecific antibody fragments (e.g. bispecific antibodies), and antibody fragments that exhibit a desired biological activity or function. The term?antibody? is used broadly and includes all monoclonal and humanized antibodies as well as chimeric and multispecific antibodies.

Antibodies can be humanized or chimeric for example. They can also be antigen-binding fractions. ?Antibody fragments? A portion of the full-length antibodies, usually the antigen binding region or variable regions. Antibody fragments can include Fab fragments, Fab? fragments, F(ab),2 and Fv fragments, diabodies, linear antibodies, single-chain antibodies molecules, and multispecific antibody molecules such as bispecific antibody molecules, which are formed by combining fragments. ?Functional fragments? The full-length antibodies retain their biological activity and a significant amount of binding to antigens. Antibodies may be “armed” By combining antibodies with other drugs, they can be ‘armed? By combining one or more drugs by covalent or another attachment, the drug can achieve greater potency and specificity.

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