https://www.biotechnologyforums.com/ Thu, 30 Apr 2026 12:43:44 +0000 MyBB https://www.biotechnologyforums.com/thread-6930.html Fri, 01 May 2015 15:27:06 +0000 MannBhargavi]]> https://www.biotechnologyforums.com/thread-6930.html designed to improve the medical knowledge, determine the efficacy of a new drug in the humans for diseases which has no certified or proven treatment/therapy, or sometimes done just for comparison with another drug for same ailment to determine whichever is more effective with lesser side effects. It also helps determine which dose/concentration of a particular drug would be best for different stages of the same disease. Clinical trials are highly crucial to be conducted before the drug is marketed to make sure the drugs are tested and certified for usage.

These studies always involve a team of experts from Medical & Pharmaceutical sectors to make sure there is compliance in trials with the protocols. The government of the country where the study is held is also involved to make sure the protocols follow the standards set by that particular government and also to make sure that the practice is ethical and patient safety is of highest importance. This study may either be interventional or observational type. In interventional, the patients or the subjects are given specific medical products as per the designed protocol by medical experts or investigators. This medical product could be drugs, devices, vaccine, etc.

In the observational studies, the interventions maybe given to a group of the population but it is mainly for the investigator to observe the health consequences or development in that group with respect to their lifestyles.

A complete clinical trial includes four main stages, collectively known as the Phases of clinical trials. The four clinical phases and drug development in each phase is defined below. However these phases may not always occur in the same chronological order. Sometimes a drug is evaluated in just 2 phases and sometimes the clinical trials may occur in such a fashion that two different phases may overlap each other.


Phase I: This is the primary stage where the first safety trials on a new drug is done in order to establish the exact dose range that is tolerated by the subjects. The dosage type maybe single or multiple. Usually this trial is conducted on severely ill patients like in cases of cancer, and in case of less ill patients, it involves pharmacokinetic studies. Pharmacokinetic studies are generally considered as phase I study.  Pharmacokinetic study can be easily defined as the study of what the body of living organism does to the drug from the moment it is absorbed by the body, distribution within the body, its metabolism to excretion.


Phase IIa: This is the first part of the 2nd phase of the clinical trial that involves the evaluation of the efficacy and safety of the drug in a group of selected population. The population here is usually patients with ailments to be treated or to prevent it. This phase concentrated on the dose-response , what type of patients are involved, Objectives may focus on frequency of intervention, dose-response, type of patient, and many other factors that are crucial in determining the safety and efficacy level. This phase may be  referred to as pilot trials.


Phase IIb: The objectives of this phase is same as that of the phase IIa, and may sometimes be referred to as pivotal trials. The conditions and factors for evaluation of efficacy and safety may also be same as phase IIa, however this phase represents absolutely thorough and careful, uncompromising display of the drug efficacy.


Phase IIIa: Phase III begins after the drug efficacy has been demonstrated but before the regulatory submission of New Drug. This phase is conducted on the group of population for whom the drug was actually intended to begin with. In IIIa clinical trials a data is generated based on both safety and efficacy but in relatively large numbers of subjects or patients in both controlled and uncontrolled trials. This trial may involve 2 group of patients for comparison of the drug interaction in the body against a placebo. This phase often provides much of the information needed for the labeling of the drug.


Phase IIIb: This phase is conducted after regulatory submission of dossier or an NDA, but prior to the drugs approval by the regulatory body and marketing of the drug. These trials may add on to earlier studies, sometimes may be the end of the clinical studies, or sometimes be directed towards Phase IV evaluations. This is the period between regulatory submission and approval of the drug for marketing authorization.


Phase IV: This phase is generally for observational purpose, but can sometimes be interventional too. This phase is conducted in order to provide with additional information about the drug’s efficacy or safety profile. Different age groups, or population from different ethnicity, races, are targeted in this phase. Previously unidentified reactions can be observed in this phase gradually adverse reactions or serious adverse effects are determined along with  related risk factors. This is very important for Phase IV because if a marketed medicine is to be evaluated for unknown indication, then those clinical trials are  considered first as interventional and then continued as Phase II clinical trials. The term post-marketing surveillance is generally used to describe the study period following the marketing of drug. During this the studies conducted are observational or non-experimental.]]> designed to improve the medical knowledge, determine the efficacy of a new drug in the humans for diseases which has no certified or proven treatment/therapy, or sometimes done just for comparison with another drug for same ailment to determine whichever is more effective with lesser side effects. It also helps determine which dose/concentration of a particular drug would be best for different stages of the same disease. Clinical trials are highly crucial to be conducted before the drug is marketed to make sure the drugs are tested and certified for usage.

These studies always involve a team of experts from Medical & Pharmaceutical sectors to make sure there is compliance in trials with the protocols. The government of the country where the study is held is also involved to make sure the protocols follow the standards set by that particular government and also to make sure that the practice is ethical and patient safety is of highest importance. This study may either be interventional or observational type. In interventional, the patients or the subjects are given specific medical products as per the designed protocol by medical experts or investigators. This medical product could be drugs, devices, vaccine, etc.

In the observational studies, the interventions maybe given to a group of the population but it is mainly for the investigator to observe the health consequences or development in that group with respect to their lifestyles.

A complete clinical trial includes four main stages, collectively known as the Phases of clinical trials. The four clinical phases and drug development in each phase is defined below. However these phases may not always occur in the same chronological order. Sometimes a drug is evaluated in just 2 phases and sometimes the clinical trials may occur in such a fashion that two different phases may overlap each other.


Phase I: This is the primary stage where the first safety trials on a new drug is done in order to establish the exact dose range that is tolerated by the subjects. The dosage type maybe single or multiple. Usually this trial is conducted on severely ill patients like in cases of cancer, and in case of less ill patients, it involves pharmacokinetic studies. Pharmacokinetic studies are generally considered as phase I study.  Pharmacokinetic study can be easily defined as the study of what the body of living organism does to the drug from the moment it is absorbed by the body, distribution within the body, its metabolism to excretion.


Phase IIa: This is the first part of the 2nd phase of the clinical trial that involves the evaluation of the efficacy and safety of the drug in a group of selected population. The population here is usually patients with ailments to be treated or to prevent it. This phase concentrated on the dose-response , what type of patients are involved, Objectives may focus on frequency of intervention, dose-response, type of patient, and many other factors that are crucial in determining the safety and efficacy level. This phase may be  referred to as pilot trials.


Phase IIb: The objectives of this phase is same as that of the phase IIa, and may sometimes be referred to as pivotal trials. The conditions and factors for evaluation of efficacy and safety may also be same as phase IIa, however this phase represents absolutely thorough and careful, uncompromising display of the drug efficacy.


Phase IIIa: Phase III begins after the drug efficacy has been demonstrated but before the regulatory submission of New Drug. This phase is conducted on the group of population for whom the drug was actually intended to begin with. In IIIa clinical trials a data is generated based on both safety and efficacy but in relatively large numbers of subjects or patients in both controlled and uncontrolled trials. This trial may involve 2 group of patients for comparison of the drug interaction in the body against a placebo. This phase often provides much of the information needed for the labeling of the drug.


Phase IIIb: This phase is conducted after regulatory submission of dossier or an NDA, but prior to the drugs approval by the regulatory body and marketing of the drug. These trials may add on to earlier studies, sometimes may be the end of the clinical studies, or sometimes be directed towards Phase IV evaluations. This is the period between regulatory submission and approval of the drug for marketing authorization.


Phase IV: This phase is generally for observational purpose, but can sometimes be interventional too. This phase is conducted in order to provide with additional information about the drug’s efficacy or safety profile. Different age groups, or population from different ethnicity, races, are targeted in this phase. Previously unidentified reactions can be observed in this phase gradually adverse reactions or serious adverse effects are determined along with  related risk factors. This is very important for Phase IV because if a marketed medicine is to be evaluated for unknown indication, then those clinical trials are  considered first as interventional and then continued as Phase II clinical trials. The term post-marketing surveillance is generally used to describe the study period following the marketing of drug. During this the studies conducted are observational or non-experimental.]]> https://www.biotechnologyforums.com/thread-6876.html Sun, 29 Mar 2015 15:47:01 +0000 jimit90]]> https://www.biotechnologyforums.com/thread-6876.html
In the clinical trials, the focus has been more on the adverse event management. The occurrence of adverse events may operate to extend the length of the trial and result in increased costs, and may be responsible, in part, for the high rate of clinical attrition, with a 40-45%failure rate experienced in Phase-III trials – where most of the failures are attributed to lack of sufficient efficacy and safety data. Building a genomic profile of the patient might help in this case.

The clinical trial process is further complicated by the need for patient monitoring, which is generally performed by doctor visiting the study or testing site.  However, such methods are not well suited for serious adverse events, requiring immediate medical attention.

Accordingly, a need exists for a remote monitoring tool that provides for early and targeted stratification of patients, which may result in improved drug success rates, increased drug response predictability, and improved identification of causal links between drug treatments and adverse events.

“Synergia” utilizes “genomics” along with “remote patient monitoring” data, stored in the cloud, use analytics to form a uniform consolidated output, thus assisting in smarter adverse event prediction.
The process may begin by building a patent gene expression database, which may involve testing the patient for inclusion and exclusion criteria.  If the patient meets the inclusion criteria, they are enrolled in the study.  The percentage of expression for a particular set of genes is calculated by means of microarray analysis (also known as SNPchip analysis).  This genetic profile database may be stored in a standardized format in the cloud. In some embodiments, the system may utilize a subscription to the cloud storage service, array plates (e.g., Affymetrix Axiom Genotyping) and a sputum sample and analysis kit, for extraction of DNA and for analysis through microarray experimentation.

The database having patient records with their gene expression level is taken into consideration for each therapy for a defined therapeutic area.  This may compare a baseline level for the gene expression defined by the user or investigator in an application to a patients’ gene expression levels and may reflect this in terms of a R-A-G (Red, Amber, Green) status, explained by means of a bar graph in a UCO page (Uniform Consolidated Output) provided through the application. The investigator may be able to identify and tag different patient clusters, depending on which category the patient belongs to (i.e., red, amber, green), which may be defined in part by the baseline value and the patients gene expression levels. This is information may be captured in a genetic predisposition database or table. By way of example, for a given therapeutic area, breast cancer, and a specific therapy, the drug Bevacizumab, some patients may respond favorably, some patients may not respond at all and yet other patients may display an adverse reaction, for example, a sudden increase in the patient’s blood pressure when the drug is administered.  These dispositions are associated with the patients’ genetic expression profile, and an investigator may use this information to identify patients who might require extra care as they may be predisposed to extreme hypertension, or in other cases may exclude the patient (who otherwise met the inclusion criterion) from the clinical study.  While the above example is context specific, the process may generally make it possible to “tag” a patient according to his or her genetic makeup.

Currently, the patients are subjected to randomization immediately after they pass for inclusion/exclusion criteria test, but without prior genetic testing done the investigator is not aware of the chance that the patient may be a “wrong patient”, which may unnecessarily increase the risk of an adverse event in the future when the drug is administered by the patient.  By “tagging” the patient, the genetic predisposition data may help to determine the “right patient for the drug” and may help to narrow down results and pin-point patients who might not be able to respond to a drug or who may give an undesirable response towards a therapy.

Once the investigator selects the patients who should be given the therapy of the drug under test, the patients may be subjected to continuous remote patient monitoring by means of vital sign monitoring through wearable devices. , information regarding the vital signs may be sent to a data platform every 20 minutes before and after a dose is given.  These readings may be captured and stored in a database maintained at the back end of the application or server in a pre-defined format.  The system may then calculate the percentage change in the average vital sign reading, at the backend,for display on the front-end application.  The percentage change may be based on a pre-dose baseline, steady state dose baseline, patient population to sub-population average, or other normative baseline for comparison.  The investigator may have the ability to set the baseline value for each parameter. Depending on the baseline value, a graph will be displayed through the UCO illustrating the percentage change in the average vital sign recording exhibited in terms of a R-A-G status.  If the percentage change of a parameter goes beyond a baseline value, an “ALERT” is displayed on the “dashboard” page of the application. By clicking the “ALERT” icon on the dashboard, the investigator may be able to select or filter those alerts based on patient commonality, for example, based on the rise of any one of the vital signs.  For example, if the percentage change in average blood pressure value is more than 35% (the baseline value set by the investigator), then the information dashboard will be populated with an “ALERT”.Clicking on the “ALERT” button may take the investigator to the UCO (Uniform Consolidated Output) page.

In current arrangements, the doctor and patient have to commonly visit the trial site to monitor the patients, record their vital signs and feed the electronic data into the system, but the risk of human error remains and the doctors predictive abilities are limited in that it fails to capture adverse events taking place between or outside of visits to a trial site.  By continuously remotely monitoring a patient, the patient is allowed to stay at home rather than remaining in a controlled clinical setting (which could reduce the cost of his maintenance), and an unexpected adverse event may be more readily detected in any of the parameter readings, because of the continuous, almost real time nature of remote patient monitoring. The system may consolidate the gene expression profile data with the real time vital sign recording data, which may help the investigator reach causal or other inferential medical conclusions, at an individual level and more broadly across trial sites.

As noted above, the investigator may be provided with a UCO that may allow him to compare the vital sign readings of a patient with the patient percentage gene expression level data, and may provide insight (e.g., through statistical analysis) into deeper relationships that may be present.  For instance, an investigator may consider the R-A-G indicator of gene expression and vital sign readings, and may match parameters and genes with similar status indicators (e.g., matching a red bar of a graph for gene expression with a red bar for a graph of percentage change in vital sign reading.  The investigator may also use the tool to identify the patients who are at a higher risk of adverse event in a quicker and more efficient manner.

As noted, the investigator may be provided with deeper insights behind the gene expression values and vital sign readings, and may look for statistically significant values that may justify making a particular decision.  In such situations, it may be useful to look at information of a broader population, and by clicking on the “gene ID” in a graph in the UCO, the investigator may be able to navigate to a site-wise depiction of the genetic predisposition data capturing the gene expression levels across sites. The investigator could use this information to form a higher level connection between a particular drug or treatment and genetic predisposition data, and may further allocate resources to patients who may need extra care or identify patients who should not be given the drug at all.

The system may serve to reduce the adverse event occurrence rate by increasing treatment predictability, which may save money in terms of compensation costs paid to patients’ family, and may even serve as evidence of a drug’s efficacy, which may help the company overcome lesser rejections and speed up the clinical trial process.

This process has been patented and is in the process of getting launched very soon in the market.]]>
In the clinical trials, the focus has been more on the adverse event management. The occurrence of adverse events may operate to extend the length of the trial and result in increased costs, and may be responsible, in part, for the high rate of clinical attrition, with a 40-45%failure rate experienced in Phase-III trials – where most of the failures are attributed to lack of sufficient efficacy and safety data. Building a genomic profile of the patient might help in this case.

The clinical trial process is further complicated by the need for patient monitoring, which is generally performed by doctor visiting the study or testing site.  However, such methods are not well suited for serious adverse events, requiring immediate medical attention.

Accordingly, a need exists for a remote monitoring tool that provides for early and targeted stratification of patients, which may result in improved drug success rates, increased drug response predictability, and improved identification of causal links between drug treatments and adverse events.

“Synergia” utilizes “genomics” along with “remote patient monitoring” data, stored in the cloud, use analytics to form a uniform consolidated output, thus assisting in smarter adverse event prediction.
The process may begin by building a patent gene expression database, which may involve testing the patient for inclusion and exclusion criteria.  If the patient meets the inclusion criteria, they are enrolled in the study.  The percentage of expression for a particular set of genes is calculated by means of microarray analysis (also known as SNPchip analysis).  This genetic profile database may be stored in a standardized format in the cloud. In some embodiments, the system may utilize a subscription to the cloud storage service, array plates (e.g., Affymetrix Axiom Genotyping) and a sputum sample and analysis kit, for extraction of DNA and for analysis through microarray experimentation.

The database having patient records with their gene expression level is taken into consideration for each therapy for a defined therapeutic area.  This may compare a baseline level for the gene expression defined by the user or investigator in an application to a patients’ gene expression levels and may reflect this in terms of a R-A-G (Red, Amber, Green) status, explained by means of a bar graph in a UCO page (Uniform Consolidated Output) provided through the application. The investigator may be able to identify and tag different patient clusters, depending on which category the patient belongs to (i.e., red, amber, green), which may be defined in part by the baseline value and the patients gene expression levels. This is information may be captured in a genetic predisposition database or table. By way of example, for a given therapeutic area, breast cancer, and a specific therapy, the drug Bevacizumab, some patients may respond favorably, some patients may not respond at all and yet other patients may display an adverse reaction, for example, a sudden increase in the patient’s blood pressure when the drug is administered.  These dispositions are associated with the patients’ genetic expression profile, and an investigator may use this information to identify patients who might require extra care as they may be predisposed to extreme hypertension, or in other cases may exclude the patient (who otherwise met the inclusion criterion) from the clinical study.  While the above example is context specific, the process may generally make it possible to “tag” a patient according to his or her genetic makeup.

Currently, the patients are subjected to randomization immediately after they pass for inclusion/exclusion criteria test, but without prior genetic testing done the investigator is not aware of the chance that the patient may be a “wrong patient”, which may unnecessarily increase the risk of an adverse event in the future when the drug is administered by the patient.  By “tagging” the patient, the genetic predisposition data may help to determine the “right patient for the drug” and may help to narrow down results and pin-point patients who might not be able to respond to a drug or who may give an undesirable response towards a therapy.

Once the investigator selects the patients who should be given the therapy of the drug under test, the patients may be subjected to continuous remote patient monitoring by means of vital sign monitoring through wearable devices. , information regarding the vital signs may be sent to a data platform every 20 minutes before and after a dose is given.  These readings may be captured and stored in a database maintained at the back end of the application or server in a pre-defined format.  The system may then calculate the percentage change in the average vital sign reading, at the backend,for display on the front-end application.  The percentage change may be based on a pre-dose baseline, steady state dose baseline, patient population to sub-population average, or other normative baseline for comparison.  The investigator may have the ability to set the baseline value for each parameter. Depending on the baseline value, a graph will be displayed through the UCO illustrating the percentage change in the average vital sign recording exhibited in terms of a R-A-G status.  If the percentage change of a parameter goes beyond a baseline value, an “ALERT” is displayed on the “dashboard” page of the application. By clicking the “ALERT” icon on the dashboard, the investigator may be able to select or filter those alerts based on patient commonality, for example, based on the rise of any one of the vital signs.  For example, if the percentage change in average blood pressure value is more than 35% (the baseline value set by the investigator), then the information dashboard will be populated with an “ALERT”.Clicking on the “ALERT” button may take the investigator to the UCO (Uniform Consolidated Output) page.

In current arrangements, the doctor and patient have to commonly visit the trial site to monitor the patients, record their vital signs and feed the electronic data into the system, but the risk of human error remains and the doctors predictive abilities are limited in that it fails to capture adverse events taking place between or outside of visits to a trial site.  By continuously remotely monitoring a patient, the patient is allowed to stay at home rather than remaining in a controlled clinical setting (which could reduce the cost of his maintenance), and an unexpected adverse event may be more readily detected in any of the parameter readings, because of the continuous, almost real time nature of remote patient monitoring. The system may consolidate the gene expression profile data with the real time vital sign recording data, which may help the investigator reach causal or other inferential medical conclusions, at an individual level and more broadly across trial sites.

As noted above, the investigator may be provided with a UCO that may allow him to compare the vital sign readings of a patient with the patient percentage gene expression level data, and may provide insight (e.g., through statistical analysis) into deeper relationships that may be present.  For instance, an investigator may consider the R-A-G indicator of gene expression and vital sign readings, and may match parameters and genes with similar status indicators (e.g., matching a red bar of a graph for gene expression with a red bar for a graph of percentage change in vital sign reading.  The investigator may also use the tool to identify the patients who are at a higher risk of adverse event in a quicker and more efficient manner.

As noted, the investigator may be provided with deeper insights behind the gene expression values and vital sign readings, and may look for statistically significant values that may justify making a particular decision.  In such situations, it may be useful to look at information of a broader population, and by clicking on the “gene ID” in a graph in the UCO, the investigator may be able to navigate to a site-wise depiction of the genetic predisposition data capturing the gene expression levels across sites. The investigator could use this information to form a higher level connection between a particular drug or treatment and genetic predisposition data, and may further allocate resources to patients who may need extra care or identify patients who should not be given the drug at all.

The system may serve to reduce the adverse event occurrence rate by increasing treatment predictability, which may save money in terms of compensation costs paid to patients’ family, and may even serve as evidence of a drug’s efficacy, which may help the company overcome lesser rejections and speed up the clinical trial process.

This process has been patented and is in the process of getting launched very soon in the market.]]>