Significance of the use of Positron Emission Tomography in Clinical Trials

PET also known as Positron Emission Tomography is a medical imaging procedure or technique which is widely used in clinical research. It is a type of nuclear medicine imaging. Nuclear imaging is a specialized area of medical imaging in which the severity of diseases or treating them is determined with the use of radioactive material. Nuclear medicine procedures are non invasive with intravenous injection as an exception which is usually painless.

PET scanners are used to produce 3-dimensional image of functional process of the human body. This helps to reveal the functioning of tissues and organs. The scanner detects pairs of gamma radiation which is emitted by the radioactive tracer given to the patient. The images will then be reconstructed by computer analysis. The radioactive tracer may be injected in the body, swallowed or inhaled as a gas depending on the area or the organ in the body to be examined. Eventually this radioactive material will get accumulated in the body organ to be scanned. Radioactive material will accumulate more in the area that has high level of chemical activity. In many clinical or imaging part of clinical trials PET images may be superimposed with CT – Computed Tomography to produce special views, it’s a practice known as image fusion. In this case, positron emission tomography will produce the functional aspect of the body (for example blood flow, use of oxygen, metabolism of glucose) while the computed tomography will produce the structural aspect of the body organs (for example lungs, liver, stomach, pelvis, and many more). Combined use of positron emission tomography and computed tomography helps as the fused images produced by this technique can pinpoint the anatomic location of any abnormal metabolic activity in the body.

A PET scan can evaluate various neurological conditions, heart problems and cancer. The radioactive tracers that accumulate in organs with high chemical activity corresponds to areas of disease and the PET scans show them as brighter spots also called as Hot Spots. A biologically active material is used for positron emission tomography. An analogue of glucose called as FDG or Fluorodeoxyglucose is injected to the subject before they are scanned. FDG is a radioactive material that is used in medical imaging and it is used only for PET scanning. The PET scanner forms images of the distribution of FDG in the body. This glucose analogue is used as it will be taken up by cells that use high glucose for examples organs like brain, kidney and also cancer cells. Cells in brain or kidney will release the glucose but cancer cells do not release the glucose once absorbed phosphorylation takes place as the metabolic activity is very high. FDG-PET helps to determine the extent/spread of certain cancers, its response to treatment and its recurrence. The types of cancer that can be detected by positron emission tomography technique are Brain, Breast, Cervical, colon, thyroid, pancreas, lung, and lymphoma. In case of heart disease PET scan can detect the blood flow to find out the possible benefits after conducting angioplasty or coronary artery bypass surgery. PET scans helps to determine the activity of brain during different tasks and further helps to determine seizures, memory disorders, epilepsy, Alzheimer’s or tumors.

To prepare for a PET scan, patients are asked to fast for 4 – 6 hours prior to scanning procedures, but are asked to consume plenty of water. Then the radiotracer will be injected into the arm or swallowed or inhaled which may take about 30 – 90 minutes to reach the target cells. For this duration the patient will be asked to rest and not move or talk. After this the patient will be scanned. Once the necessary part of the body is scanned the patient is again asked to consume plenty of water so as to flush the radioactive tracers out of the body more quickly. It may take about 3 – 4 hours for the radioactive tracers to completely leave the body system. It’s not recommended for pregnant women to undergo PET scanning as there is a risk for the baby.

PET – Positron Emission Tomography is used in the imaging part of a clinical trial in studies on Hodgkin’s or non-Hodgkin's lymphoma, colorectal, lung, breast cancer and melanoma. It is also used in pre-clinical studies in animals in order to facilitate repeat investigation in the same subject, thus helping in oncology research studies leading to an increase in statistical quality of the data and substantially decreasing the number of animals required for any given study. Thus using PET scanner for clinical trials is a valuable technique.

Clinnovo is a clinical innovation company. It is pioneer CRO industry in India. Clinnovo offers professional Clinical Research Course, clinical data management course , SAS and imaging training. Clinnovo has been serving different bio-pharma industries across the world with excellence and high quality. For more information contact at +91 9912868928, 040 64635501

Electrocardiogram (ECG) and its significance in Clinical trials

Electrocardiogram is a non-invasive and painless test used to record electrical impulses of the heart. To measure the electrical activity of the heart, electrodes will be attached onto the skin and a device external to the body records the activity. Apart from measuring the electrical activity of the heart, electrocardiogram can also measure the position and size of the heart chambers as well as if any damage to the heart is present and therefore this test is also used for drug trials.

There are two phases in each cardiac cycle or heart beat, contraction and relaxation. When the two ventricles relax the atria contracts and when the atria relax, the ventricles contract. The contraction is called as systole and the relaxation is called as diastole. Thus the two phases constitute a systole and diastole of both ventricles and articles. A system of nerve fibers controls the filling up and emptying of the heart chambers. This system of nerve fibers supply electrical stimulus to spark the contraction of the heart muscle.

Alterations in the electrical system of the heart may cause serious or life threatening consequences. In such a situation, the heartbeat can be regulated by implanting an artificial pacemaker. The sinoatrial and atrioventricular nodes act as the natural pacemakers of the heart. In an electrocardiogram test, problems with the heart rhythms and the conduction of heartbeat, can be recorded and produced on a paper. These parameters are measured as it can reveal if the heart is affected by an underlying heart condition or heart disease. Performing electrocardiogram depends on what is being measured. The test is in most cases performed when the patient is resting. The test can also be done while the patient is on an exercise bike or treadmill, done usually if the patient displays symptoms that relate to coronary heart disease.

Electrocardiogram test is used in case of symptoms such as difficulty in breathing, chest pain, angina, palpitations or abnormal heartbeats. Electrocardiogram helps to indentify if the patient has coronary artery disease. It also helps to identify if there is thickening of heart muscle.

To prepare for the test, the health care provider should be informed about the medication the patient is taking, as there are chances that these medications may interfere with the results. Drinking cold water immediately before taking electrocardiogram test may lead to false results.

When electrodes are first applied, it may feel cold. Some people could develop  rash or irritation where the electrode patches are attached, but it is quite rare . Normal heart rate is 60 to 100 beats per minute and normal heart rhythm is consistent and even.

Abnormal electrocardiogram results might be a sign of arrhythmias, congenital heart defects, change in the amount of potassium and sodium in the blood, past or current heart attack, myocarditis, poor blood supply to the arteries of the heart, atrial fibrillation, heart failure and many more.

Electrocardiogram test is not risky, and since no electricity is sent through the electrodes there is no risk of shock. The condition being tested determines the accuracy of the electrocardiogram test. It is not a hard and fast rule that a heart problem has to show up on taking electrocardiogram test as some heart defects or problems may not lead to any specific changes in ECG.

In clinical trials this test may be used to examine the success of the drug treatment. Most of the times, the test is used for research or diagnostic purposes on human hearts. As new regulatory guidance have rapidly emerged and its global acceptance, cardiac safety has become the prime concern in any new drug development during the recent years.

Clinnovo is a clinical innovation company. It is pioneer CRO industry in India. Clinnovo offers professional Clinical Research Course, clinical data management course , SAS and imaging training. Clinnovo has been serving different bio-pharma industries across the world with excellence and high quality. For more information contact at +91 9912868928, 040 64635501

JANUS

JANUS is the roman god for gates or doors. With the two faces, he is supposed to depict data and knowledge.

From FDA point of view they are swamped with data in paper format, now that is almost impossible to do anything remotely smart with paper. Out of this need came out JANUS:

Part of an agency initiative to enhance decision making through improved management of study data

• Improved access to data
  
• Standardization of data including vocabulary
  
• User friendly tools
  

Goal is to improve analysis of data From data in a single study

• to data across multiple studies in a single submission
• to data across multiple submissions

At this point JANUS is meant to be a comprehensive data model that can deal with many different types of data and meta dataJanus is meant to be a comprehensive data model that can deal with many different types of data and meta data.

JANUS is still in implementation phase and we see at as an confusion between HL7 and CDISC. We will soon discuss on this mess with HL7 and CDISC.

// This has been a contribution of Clinnovo Research Labs at http://www.clinnovo.com. We appreciate your comments and feedback.

What the heck is xml ?

XML or extensible markup language is exactly what the acronym says. XML is a non-proprietary textual representation of data/strings and atributes.

XML structure is defined by a schema or a DTD (document type definition). There are a number of clinical research/health care standards based on xml such as HL7, CDISC, JANUS etc.,

XML basically defines content/data as tags and attributes and data elements can be defined in namespaces. The intention of this post is not to teach you xml but to give some basics of why you should be aware of xml in relation to Clinical Research.

Recently Microsoft has been in conflict with many open source groups in relation to their OOXML standard, There has been complaints and concerns that this standard has been rigged.

We will discuss about JANUS in our next post.

FDA website gets a facelift

Now we all did visit the FDA website and felt it was a bit out-of-fashion. FDA has listened to us and have come up with new look website, check it out at www.fda.gov.

One thing : The new look is only for the first page, rest of the FDA site is exactly like you saw many many years back....

CDISC ADaM standard

ADaM is a CDISC standard to submit analysis data to FDA. Key is to understand that ADaM is a SDTM model for providing analysis data, programs and data definitions. The principles of ADaM is aimed at providing  a clear and unambiguous  communicationof the content, source and  quality of the datasets submitted in support of  the statistical analysis performed by the 
sponsor. This in turn would support the machine-readable  description for the JANUS data repository. 

Analysis datasets

Analysis datasets are datasets created to support specific analyses.

• Each dataset is provided as a SAS Transport (XPORT) file. 
• Programs should be provided as both ASCII text and PDF files and should include sufficient documentation to allow a reviewer to understand the submitted programs. 

Programs

Programs are scripts used with selected software to produce reported analyses based on these datasets.

Analysis-level Metadata

• ANALYSIS NAME –A unique identifier for this analysis. May include a table number or other sponsor- specific reference. 
• DOCUMENTATION –A text description documenting the analysis performed.
• REASON –The reason for performing this analysis. Examples may include Pre-specified, Data-driven, Exploratory, and Regulatory Request. 
• DATASET –the name of the analysis dataset used should be linked to the analysis dataset used for this analysis. In most cases, this will be a single dataset. If multiple datasets are used, they should all be listed here. 
• PROGRAM –Analysis programs using the DATASET above as input can be described or included here.

The complete ADaM specification can be found at : http://www.cdisc.org/models/adam/V2.0/index.html

define.xml and SDTM

Define.xml is the document which specifies the standard for providing Case Report Tabulations Data Definitions in an XML format for submission to regulatory authorities (e.g., FDA). 

The XML schema used to define the expected structure for these XML files is based on an extension to the CDISC Operational Data Model (ODM).

In the picture below the key aspects are highlighted with the red text, basically it is a listing of data items that a sponsor will transmit to FDA along with the regulatory application.

Each data set if furthered detailed with what data items are sent and their nature (ex: Derived or from a CRF page)

You can find the DTD definition and stylesheets to transform define.xml on CDISC website : http://www.cdisc.org/models/def/v1.0/index.html

CDISC ODM Standard

The Operational Data Model (ODM) provides a format for representing the study metadata, study data and administrative data associated with a clinical trial.

It represents only the data that would be transferred among different software systems during a trial, or archived after a trial.

It need not represent any information internal to a single system, for example, information about how the data would be stored in a particular database.

The ODM model assumes that a study's clinical data will consist of several kinds of entities. These include:

• subjects
• study events (a series of forms connected to an event)
• forms (aggregations of item groups)
• item groups (groups of items that will be analyzed together)
• items (single data item such as Hb%)
• annotations (comment applied to any of the above)

CDISC SDTM standard

Inline with the Critical Path Initiative CDISC has developed three main standards to improve the efficiency of clinical trial projects, namely : Operational Data Model (ODM), the Study Data Tabulation Model (SDTM) and the Analysis Data Model (ADaM).

The SDTM defines a standard structure for study data tabulations. These are to be submitted as part of a product application to a regulatory authority such as FDA.

The SDTM was prepared by the CDISC Submission Data Standards (SDS) Team to guide the organization, structure, and format of tabulation data sets for study data submitted to regulatory authorities. Data tabulation data sets are one of four ways to represent the human subject Case Report Tabulation (CRT) and equivalent animal data submitted to the FDA.

The SDTM is composed of 30+ defined domains within six broad categories. Each domain represents a file structure and contains a particular type of data associated with clinical trials, such as demographics, vital signs or adverse events.

The model also provides the ability to create custom-defined domains with sets of standard variable definitions. Variables in common across domains all have similar name extensions, and the standard specifies the beginning prefix of all variables be a (typically) two-letter domain abbreviation.

We will come back with a discussion on how to interface your CDM system to produce SDTM files.

CDISC discussion forums : http://www.cdisc.org/discussions/discussions.html

CDISC

CDISC mission statement from CDISC website says "CDISC is a global, open, multidisciplinary, non-profit organization that has established standards to support the acquisition, exchange, submission and archive of clinical research data and metadata. The CDISC mission is to develop and support global, platform-independent data standards that enable information system interoperability to improve medical research and related areas of healthcare.  CDISC standards are vendor-neutral, platform-independent and freely available via the CDISC website."

We will cover each CDISC standard in detail in the coming posts, here is a summary table with links to the current standard specification at http://www.cdisc.org. To give an overview the different parts of the CDISC standard are related as below to the clinical trial process

CDISC Standards in Production

Submission Data Standards Team (For submission of data-sets to regulatory)	(SDTM IG V3.1.1) (SDTM V1.1) (SDTM IG V3.1) WebSDM edit checks for  (SDTM 3.1.1)
Operational Data Modeling Team	(ODM V1.3) (ODM V1.2.1) See also (eSDI Document)
Analysis Dataset Model Team	(ADaM 2.0)
Laboratory Standards Team	(LAB)
Standard for Exchange of Non-clinical Data	(SEND V2.3)
Case Report Tabulation Data Definition Specification (define .xml)	(CRT-DDS V1.0)
Terminology	(Terminology)

Standards in Development

Submission Data Standards Team	SDTM IG V3.1.2 Draft SDTM V1.2 Draft Metadata Submission Guidelines, Appendix to the SDTM IG V3.1.1
Protocol Representation Group	(PRG)
Clinical Data Acquisition Standards Harmonization (CDASH)	(CDASH)
Terminology	(Terminology)
Cardiovascular and Tuberculosis Data Standards	(Cardiovascular and Tuberculosis Data Standards)

Electronic Health Records (EHR) in clinical trials

Electronic Health Records (EHR) are standard instruments used to capture patient encounter data in clinical practice. They offer some key benefits in relation to clinical trials by supporting : 1. Increased patient recruitment, 2. Increased physician participation.

Study Set-up

• Query EHR database to establish number of potential study candidates.
• Incorporate study manual or special instructions into EHR “clinical content”for study encounters

Study execution

• Incorporate study-specific data capture (just as you would do with a CRF in a clinical trial) as part of routine clinical care / clinical documentation workflow.
• Auto-populate study data elements (for example demographics) into CRFs from other parts of the EHR database.
• Embed study-specific data requirements (modules not already included in the EHR) as special tabs/documentation templates using structured data entry.
• Implement rules/alerts to ensure compliance with study data collection requirements (EHR systems have inbuilt validation checks)
• Create range checks and structured documentation checks to ensure valid data entry

Study Enrollment

• Implement study screening parameters into patient registration and scheduling.
• Query EHR database to contact/recruit potential candidates and notify the patient’s provider(s) of potential study eligibility.

Submission & Reporting

• Provide data extraction formats that support data exchange standards (for example CDISC)
• Document and report adverse events (Note : EHRs often use ICD-9/10 coding, while CRFs would need MedDRA codes)

FDA regulations on eClinical trials

The following general guidelines are proposed by FDA in reference in Computerized systems in clinical trials, the complete document is available at http://www.fda.gov/ora/compliance_ref/bimo/ffinalcct.htm

A. Each study protocol should identify at which steps a computerized system will be used to create, modify, maintain, archive, retrieve, or transmit data.

Comment : This means that the study protocol has to receive input from the data manager. Most of the companies include these steps as SOPs so that they can be referenced in the study protocol.

B. For each study, documentation should identify what software and, if known, what hardware is to be used in computerized systems that create, modify, maintain, archive, retrieve, or transmit data. This documentation should be retained as part of study records.

Comment : This level of detail is not mandatory, and is often missed out in most study protocols.

C. Source documents should be retained to enable a reconstruction and evaluation of the trial.

Comment : This requirement is fulfilled via a Audit trial so that FDA/ independent audits can be performed.

D. When original observations are entered directly into a computerized system, the electronic record is the source document.

Comment : The specific condition where this rule will not apply is for lab data, the source data is obtained electronically from the lab. The data is then batch loaded into the CDM system, still the source data is the lab data.

E. The design of a computerized system should ensure that all applicable regulatory requirements for recordkeeping and record retention in clinical trials are met with the same degree of confidence as is provided with paper systems.

Comment : 21 CFR Part 11 and ER/ES are two common regulatory requirements. The "degree of confidence" is set via a validation process for each CDM system.

F. Clinical investigators should retain either the original or a certified copy of all source documents sent to a sponsor or contract research organization, including query resolution correspondence.

Comment : Though this sounds simple, it is complicated for investigators to maintain a source data archive.

G. Any change to a record required to be maintained should not obscure the original information. The record should clearly indicate that a change was made and clearly provide a means to locate and read the prior information.

Comment : All updates on source data will include a reason for change, data and time of change, person initiating the change, data value before change and data value after change. Sometimes the change in data may require sign-off by a study manager.

H. Changes to data that are stored on electronic media will always require an audit trail, in accordance with 21 CFR 11.10(e). Documentation should include who made the changes, when, and why they were made.

Comment : Refer to above

I. The FDA may inspect all records that are intended to support submissions to the Agency, regardless of how they were created or maintained.

Comment : Refer to above

J. Data should be retrievable in such a fashion that all information regarding each individual subject in a study is attributable to that subject.

Comment : Refer to above

K. Computerized systems should be designed: (1) So that all requirements assigned to these systems in a study protocol are satisfied (e.g., data are recorded in metric units, requirements that the study be blinded); and, (2) to preclude errors in data creation, modification, maintenance, archiving, retrieval, or transmission.

Comment : Refer to above

L. Security measures should be in place to prevent unauthorized access to the data and to the computerized system.

Comment : Refer to above

Data integration

Data Integration has become a major (and unsolved) challenge in the realm of clinical trials. As the means to electronically capture and store the data from clinical trials in large databases became easy the data started pouring in from several sources and different formats.

For example, the use of third party applications like IVRS, ePRO, CDMS, CTMS and AERS systems is a great challenge since they could come from different vendors and use their own internal proprietary data formats.

Another key area is laboratory data integration. Often the lab data comes from a LIMS or a data dump from the lab. This data has to be integrated with rest of the trial data. There is also a temporal dissociation between clinical data and lab data.

Often the issue becomes more challenging due to anonymization or coding. Each patient has to be identified by the same unique identifier across different systems to make integration feasible.

In the next couple of posts we will discuss about CDISC and the emergence of standards to support data integration.

Electronic Pens

Electronic pens and other forms of mobile data entry have gained recent prominence in clinical data collection. The reasons have been quite obvious paper based forms in combination with electronic data entry (so called hybrid approach) resulted in double data entry and significant error rate. This opened up the scenario for data to entered and stored in a single instance in a field based setting.

Currently four different technology options are available :

1. Use a Tablet PC (cuts you a cheque for 2500 USD) and a software for CRF design
2. Use a Paper on Pen (costs around 150 USD, check logitech io pen)
3. Use PDA digitizer, basically you write on paper and that information is digitized real-time
4. Use a PDA directly, works if you have a small CRF and limited number of fields

When we did a pilot in our ongoing clinical study it looked not-so-practical. Our trial subjects (we have 50-70 year olds) often forgot to record in this electronic diaries and there was no way for them to go back retrospectively (which you could do in a regular paper diary). However electronic means of recording data were acceptable, and to reduce cost on our trial subjects we had to "lease" them out for the duration of the trial.

Interactive Voice Response (IVR)

Pharmaceutical companies continue to seek ways to reduce resource cost and financial risk by using diverse technology solutions. As you know one of the areas of clinical trial business that has a logistic complexity and resource overhead is Trial management.

Interactive Voice Response Systems (IVRS) solves two key aspects : 1. Drug supply chain management and 2. Subject recruitment . A more recent application has been use in advertising directly to trial participants.

Basically IVRS uses telephone as a input device. When a person calls into the number (usually a toll free number) they would be given a series of prompts to choose from and directed to a specific service they would wish to obtain.

Drug supply chain management

IVRS manages medications on a dispensing model, rather than a subject specific model used in regular clinical practice. By being medication-dose centric IVRS can help patients to interactively order trial medications. Note that the patient would come to the clinical site and the investigator or study coordinator would order the required medication. Each order would trigger a electronic message to the drug inventory database, and if the stocks go below certain threshold it can send a fax/email to the stock manager.

Subject recruitment

IVRS can be used to collect data from subjects during recruitment as well as during the study progress.

Integration

IVRS systems are now fully integrated with both the EDC systems and trial logistics systems. This gives lot of benefits to both sponsors and trial participants.

Electronic Data Capture (EDC)

EDC means different things when used in different parts of the clinical trial process/operations. The overall objective is to skip or combine paper based data capture with electronic means. EDC has become a "standard practice" in large pharma companies moving up from around 20% in 2005 to more than 45% in 2007 which translates to a $3.1 billion market for 2006-2011.

The (purported)  benefits of EDC according to HealthInsights EDC report (available online) :

1. Reduction in time from last patient visit to database release
2. Reduction in the number of required queries
3. Efficiency gains from the reuse of forms
4. Reduction in site-monitoring costs
5. Reduction in project management costs
6. Reduction in time surrounding patient enrollment tracking

Now, that huge a market definetly attracts lot of players, a ball-park figure for number of EDC vendors would be more than 100, with 20 or so having a decent market share.  The list of vendors is large and includes:

1.  PhaseForward
2. DataTrak
3. eTrials
4. Medidata Solutions 
5. Oracle
   
6. Akaza Research (OpenClinica)
7. InferMed (actually a decision support software vendor)

If you would like to build your own EDC system please refer to FDA guidance on this at this website. Independent of which company you work with (by the way Excel or Access would not count towards EDC) you will be faced with one EDC system or more. So we will make it point to elaborate on the different vendors and their key strengths in future posts. 
 

eClinical : The Future of Clinical Trials

eClinical has become the latest buzz word and a blessing with advanced technology to support clinical trial management with increased speed, improved efficiency and reduced cost. In the next series on eClinical we will write on the following topics :

1. Electronic Data Capture (EDC)
2. Interactive Voice Response (IVR)
3. eMonitoring
4. eDiary
5. Electronic Pens
6. Data integration
7. FDA regulations on eClinical trials
8. Electronic CRFs (eCRFs)
9. Clinical Trial Management systems (CTMS)
10. Electronic Health Records (EHR)
11. CDISC

Technology to support Patient Adherence in Clinical Trials

One of the major issues in Clinical research and analysis is adherence (or compliance) of patient's to the clinical trial protocol. This is especially an issue in evaluation of PK/PD, safety, efficacy and dose estimation. 

Currently most of the compliance issues are passively handled and patients are considered "censored" when they drop out from the study. This leads complexities in statistical interpretation and reporting. However there has been a recent surge in new technology that is aimed to measuring adherence and improving it.

Compliance process can be initiated by using direct communication methods such as telephone, email and fax etc., Another important aspect is patient education and interaction at different levels including the pharmacist. 

Currently the most advanced technology for monitoring compliance in taking the drug is use of biosensors based on RFID sensor devices that provide a disposable, inexpensive, state-of-the-art method. Another method is using drug tagging to track usage.

DIA is organizing a conference on this topic in May 2008 :http://www.diahome.org/DIAHOME/Education/FindEducationalOffering.aspx?productID=16491&eventType=Meeting

Biometrics

From Wikipedia the term Biometrics has two meanings, 

Biometrics (ancient Greek: bios ="life", metron ="measure") refers to two very different fields of study and application. The first, which is the older and is used in biological studies, including forestry, is the collection, synthesis, analysis and management of quantitative data on biological communities such as forests. Biometrics in reference to biological sciences has been studied and applied for several generations and is somewhat simply viewed as "biological statistics."

More recently and incongruently, the term's meaning has been broadened to include the study of methods for uniquely recognizing humans based upon one or more intrinsic physical or behavioral traits.

In comes another colloquial term "Biometrics" used by CROs and Clinical research organizations can mean anything from Biostatistics, Statistical Programming, and Clinical Data Management. One common usage is to indicate number of days before database was locked following Last Subject Last Visit (LSLV), and what percentage of studies were finalized according to plan etc.,  

May be it is time to stop using this term and directly refer to what we meant whether it is finger printing or statistical reporting or database locks that we are talking about !!!