Permission System Advantages

The integration of the new permission system into Cleo allows us to:

1. Know who is logged into the application.
2. Know what requests users have made to the application, and provides a log of those requests.
3. Check that staff members have permission to view, add, change and/or update information in the database.
4. Create permissions that meet the needs of the organization using Cleo.

Permission System Roll-out

The permission system is being rolled out in phases.

• The first phase involved implementing the permission system in the administrative application admin, implementing the creation and control of staff member accounts and their permissions, and creating a reset password application to allow users to reset their passwords.
• In the second phase, the permission system was implemented in the Explore application. Each request by a staff member is checked by the permission system.
• In the third phase, the permission system will be implemented in the Operations application. Finer control of staff member permissions will be available to Cleo’s administrators.

Treatment queries are under the Query tab in Cleo’s Explore application; see Figure 1. Creating a Treatment query is a two step process. First the contents of the treatment table are selected. Then, the treatment table is filtered.

Figure 1
Queries Tab in Cleo’s Explore Application

Queries tab in Colabrativ’s Clinical Entry and Operations (Cleo) Explore application before the creation of any treatment tables, or any queries have been run.

Selecting Treatments Table Content

Treatments in the treatments tables are grouped by patient, and chronologically ordered by the start date of each treatment. There are a number of options that control the contents of a treatments table; each option is reviewed below.

Treatment Table Options

Option	Description
Treatments Included	Single Treatment adds a single treatment to each row in the treatments table, and is the default for the Treatments Included option. The Treatment and Post-treatment option adds both a treatment and the next treatment (post-treatment) to each row of the treatments table. If the treatment is the last treatment and if a Deceased or Last Contact or Lost to Follow Up event is after the last treatment, then the Deceased or Last Contact or Lost to Follow Up event is added as the post-treatment. The Pre-treatment to Post-treatment option adds three treatments to each row in the treatment table. As with the Treatment and Post-treatment option above, Deceased or Last Contact or Lost to Follow Up events can be the final “post-treatment” for a patient. The All Treatment option puts all of a patient’s treatments in a single row. As with the Treatment and Post-treatment and Pre-treatment to Post-treatment options above, Deceased, Last Contact or Lost to Follow Up events can be the final “post-treatment” for a patient.
There are five therapy types that can be included in a treatments table.
Include Chemotherapies	If checked, chemoetherapy events will be included in the treatments table.
Include Complementary Therapies	If checked, complementary therapy events will be included in the treatments table, such as treatments with Curcumin.
Hormone Therapies	If checked, hormone therapy events will be included in the treatments table, such as treatments with Tamoxifen.
Include Immunotherapies	If checked, immunotherapy events will be included in the treatments table.
Include Vaccines	If checked, vaccine events will be included in the treatments table, such as MUC1 Dendritic Cell Vaccine treatments.
The next four Include options add additional information to the treatment table, including the patient’s immunohistochemistry (IHC) and genetic results.
Include Agent 0 1 Columns	If checked, agent columns will be added to the treatments table. Each treatment agent in a treatment will have a 1 in the column labeled with that agent’s name. This option was designed to facilitate cluster analysis.
Include IHC Results	If checked, the H-score for each IHC test run on the patient’s specimen collected just prior to the treatment. e.g. pretreatment specimen, will be added to a column that uses the IHC test code as the column header.
Include Full IHC Results	If checked, the intensity, percent positive cells and H-score for each IHC test run on the patient’s pretreatment specimen will be added to the columns that use the IHC test code as prefix for the column header.
Include Genetic Results	If checked, the results for each genetic test, such as polymerase chain reaction (PCR), fluorescent in situ hybridization (FISH) or next generation sequencing run on the patient’s pretreatment specimen will be added to a column that uses the test code as the column header.
There are a number of situations in which one might not want to include the next treatment in a table. The next five options allow one to merge a number of difference treatment types into the treatment added to the treatments table.
Merge Neoadjuvant Treatments	If checked, neoadjuvant treatments will be merged with the following treatment. The start date of the neoadjuvent treatment will be used as the start for the merged treatment, if it is before the start of the treatment. A Neo flag will be added to the Flag column when a neoadjuvent merge is performed.
Merge HIPEC Treatments	If checked, Heated Intraperitoneal Chemoperfusion (HIPEC) treatments will be merged with the following treatment. The start date of the HIPEC treatment will be used as the start for the merged treatment, if it is before the start of the treatment. A HIPEC flag will be added to the Flag column when a HIPEC merge is performed.
Merge Maintenance Treatments	If checked, maintenance treatments will be merged with the previous treatment. The end date of the maintenance treatment will be used as the end date for the merged treatment, if it is after the end date of the treatment. A Main flag is be added to the Flag column when a maintenance merge is performed.
Merge Continuation Treatments	If checked, continuation treatments will be merged with the previous treatment. The end date of the continuation treatment will be used as the end date for the merged treatment, if it is after the end date of the treatment. A Cont flag is be added to the Flag column when a continuation merge is performed.
Simultaneous Treatments	If checked, treatments that overlap in time, but are of different treatment event types, e.g. a chemotherapy and a hormone therapy, will be treated as simultaneous. The agents in the simultaneous treatment will be added to an inserted Simultaneous Agents column.

Treatments Table Creation

Once treatments table options have been selected, the table can be created without applying any filtering to it by clicking on the “Create” button; see Figure 2. This is the only action that can be taken for the “All Treatment” Treatments Option. The treatments table creation options are disabled after a treatments table has been created, but the options used to create the treatments table are still displayed.

Prior to the creating the treatments table it is a good idea to supply a title in the “Query Title” box. The title may also be added after creating the table by filling in the “Query Title” box and clicking the “Update Title” button.

Once the treatments table has been created, it can be downloaded as a tab separated values (TSV) table by clicking on the green link. For the All Treatments table in Figure 2, the link is PatientTherapies_2013-11-29_09-45-05.tsv.

Figure 2
Queries Tab in Cleo’s After Creating an All Treatments Table

The Queries tab in Colabrativ’s Clinical Entry and Operations (Cleo) application after creating an All Treatments table. The treatments table creation options have been disabled, but still display the options that were selected when creating the treatments table, PatientTherapies_2013-11-29_09-45-05.tsv.

Filtering the Treatments Table

Filters are applied to a treatments table by selecting a filter from the “Select Filter” pull-down menu. There are a number of filters that can be applied to a treatments table. Each filter is shown below.

Treatment Table Filters

Once an agent name has been entered in the Chemotherapy Agents box, a new box will be created for an additional agent name. If the wild-card (*) is added as an agent then the filter will not remove treatment rows that match the agents supplied, but table row may have additional agents. Without a wildcard, the number of agents must match the number of agents supplied in the filter.

After setting up the desired filters for treatments table click on the “Run Query” button. The filtering will be applied to a preexisting treatments table, or a new treatments table will be created from the treatments table options which have been selected. The starting treatments table can be downloaded using the green link supplied for it. See Figure 3, in which the start treatment table link is Treatments_2013-11-28_11-08-16.tsv. The number of patients, specimens and treatments are provided for before and after the filtering. The filtered table can also be downloaded using the green link supplied for it. See again Figure 3, in which the query results table link is Query_2013-11-28_11-08-16.tsv.

Figure 3
Queries Tab in Cleo’s After Filtering Treatments Table

The Queries Builder after using a specimen type filter of O and P on a treatments table. The treatments tables created before and after filtering are Treatments_2013-11-28_11-08-16.tsv, and Query_2013-11-28_11-08-16.tsv, respectively.

Multiple filters can be run at the same time by simply selecting another filter from the “Select Filter” pull-down menu. After a Query has been run, additional filtering can be performed. For example, one might want to first filter on Cancer Codes and then Patient Histologies initially, and then to use the resulting filtered treatments table as the starting table for several treatment agents filterings.

Select Query

Just below the Query Builder banner is the “Select Query” pull-down menu (see Figure 3). All of the queries that have been run are displayed in this pull-down menu with their time-stamps plus their queries titles. To clear the query, an empty query can be selected from the “Select Query” pull-down menu. When a query is selected, the Query Builder panel will be cleared and replaced with the selected query’s information.

I will be participating in Wheel to Survive, a 6 hour indoor cycling event, to raise money for The Clearity Foundation, which helps ovarian cancer patients and their physicians make better-informed treatment decisions based on the molecular profile of the tumors.

Ovarian Cancer

Ovarian cancer is the most lethal gynecological cancer affecting 1 in 70 women.  Today more than 70% of ovarian cancer patients will die of their disease, compared to less than 20% of breast cancer patients.  When ovarian cancer is detected and treated early, the five year survival rate is greater than 92%.  Sadly though, symptoms are vague and subtle, so most patients are diagnosed at later stages and less than 50% will survive longer than 5 years after their diagnosis.

The Clearity Foundation

The Clearity Foundation, a 501 (c)(3) organization, supports women battling ovarian cancer by providing personalized information to individualize treatment decisions.  By providing tumor blueprints to patients, Clearity is bringing the future of cancer treatments to women who need help today.

Wheel to Survive Fundraising

Wheel to Survive fundraising is a 6-hour indoor cycling event sponsored by the Be The Difference Foundation.  Be The Difference Foundation mission is to help women increase their chance of survival of ovarian cancer.

How You Can Help

I truly appreciate any support you can provide.  It will benefit a great cause.   You can also help me reach my goal by sharing this page on Facebook and Twitter.  Or, send an e-mail to friends you think might be interested in contributing and include a link to my page.  Sign up and ride with me.  Thank you for your generous support and joining me to Be the Difference in the fight against ovarian cancer.  Our mothers, daughters, sisters, grandmothers and girlfriends are counting on us.

Colabrativ, Inc.’s Clinical Entry and Operations Application

For the past two years, Colabrativ, Inc. has been working with The Clearity Foundation to build a custom enterprise application to store and manage the clinical information gathered while profiling a patient's tumor.  The application, Clinical Entry and Operations (Cleo) was put into production on October 30, 2012.  More information on Cleo is available by viewing my blogs on The Clearity Foundation is in Production with Colabrativ’s Clinical Entry and Operations and Cleo (Clinical Entry and Operations) Version 2 Released.  The Clearity Foundation staff logs about five hours of work for each patient they profile.  Our goal is to lower the number of hours per patient, so that the foundation can help more patients.

I appreciate your support,
Marc Whitlow, Ph.D.
President and CEO
Colabrativ, Inc.

State of California Supplier # 1753901

Colabrativ is a custom software development company, with experience in clinical operations and biomedical research & development. We are looking to collaborate with companies that are doing business with the State of California.

Software Development

Projects

• Clinical Entry and Operations (Cleo)
• iExperiment – Enterprise Electronic Notebook

Clients and Collaborators

Medical Record Summaries

Our goal for Cleo version 2 was to migrate Clearity’s patient medical record summaries from a Microsoft Access database to Cleo. In the process, we built medical record-specific objects to handle the specific needs of each class of medical record. To meet the foundation goals each medical record event has two display modes in a chronological list under the History tab. The “single” line display summaries the most important information, such as a CA-125 diagnostic procedure result, see Figure 1. The detailed display mode can be quickly accessed for any history event, by clicking on the Green “Open Panel” button on the left side of each history event box.

Figure 1
History Tab in Cleo Application “Single Line” Display Mode

History tab in Colabrativ’s Clinical Entry and Operations (Cleo) application displaying a fictitious ovarian cancer patient history in single line display mode. All of the personal information displayed in this figure is fictitious, and does not represent a real individual or their medical history.

All history events have a common set of information about the event, including: date of the event, notes on the event and the source of the information. The source of the information can be: Medical Records, Pathology Reports, Imaging Records, Patient and Physician Communications. The source of the information can be uploaded into the history event, and are securely stored on an encrypted drive.

Both display modes have access to any medical record documents that have been uploaded in a history event. In the “single” line mode a file icon can be clicked on to download the medical record file. In the detailed display mode the full name of the file is a download link to the file, see Figure 2. Multiple files can be uploaded for any history event. This is commonly done for surgical records and their associated pathology reports.

Diagnostic Procedure

A diagnostic procedure, such as the determination of the patient CA-125 level, used to monitor ovarian cancer patient response to therapy. In addition to the basic information described above, a Diagnostic Procedure history event has information on the test used, and its result. If there is evidence for any change in the patient’s status then that information is collected, along with who made the determination that the patient status had changed.

Figure 2
Single Line and Detailed Displays of Diagnostic Procedure History Event

A fictitious ovarian cancer patient Diagnostic Procedure history event shown in single line display mode (A) and detailed display mode (B) in Colabrativ’s Clinical Entry and Operations (Cleo) application. All of the personal information displayed in this figure is fictitious, and does not represent a real individual or their medical history.

Imaging Procedure

An Imaging Procedure history event has information on the procedure type, the Body Region imaged and the observations made from the images. Like Diagnostic Procedure events, an Imaging Procedures can have “Evidence For” any change in the patient’s status.

Figure 3
Detailed Displays of Imaging Procedure History Event

Imaging Procedure history event shown in detailed display mode in Colabrativ’s Clinical Entry and Operations (Cleo) application. All of the personal information displayed in this figure is fictitious, and does not represent a real individual or their medical history.

Biopsy and Centesis

Both Biopsy and Centesis history events use the same panel structure. In addition to the basic information described above, these history events have information on the procedure used, and if there was evidence for any change in the patient’s status. In addition, the pathological analysis of any material collected, e.g. Cancer type, Histology, Stage and Grade can be entered. If the pathological analysis is the “Patient’s Staging Information Source”, then one can check this box and the patient’s Summary at the top of the history will be populated with this information. This option is also available for surgical events.

Figure 4
Detailed Displays of Biopsy History Event

A fictitious ovarian cancer patient Summary and Biopsy history event shown in the detailed display mode in Colabrativ’s Clinical Entry and Operations (Cleo) application. All of the personal information displayed in this figure is fictitious, and does not represent a real individual or their medical history.

Surgery

Surgery history events are similar to Biopsies and Centeses, in that they all can have pathological analysis of any sample collected, e.g. Cancer type, Histology, Stage and Grade can be entered, and that information can be used to populate the patient’s Summary. They differ in that multiple procedures can be performed during a surgery, and they do not have “Evidence For” patient change in the status option.

Figure 5
Detailed Displays of Surgery History Event

Surgery history event shown in the detailed display mode with an uploaded medical record and pathology report in Colabrativ’s Clinical Entry and Operations (Cleo) application. All of the personal information displayed in this figure is fictitious, and does not represent a real individual or their medical history.

Chemotherapy

Chemotherapy events contain information on the chemotherapy agents used and the cycles of chemotherapy that were performed. A typical chemotherapy cycle is three consecutive weeks of treatment, followed by a week off. The cycle information is traced using the first to last cycle. This allows for changes in treatment, such as dropping an agent after the first cycle and replacing it with a new agent on the second cycle or when a drug dose is lowered. Some patients are enrolled in clinical trials, in which one may not know what treatment the patient received, due to the blind nature of the clinical trial.

Figure 6
Detailed Displays of Chemotherapy History Event

Chemotherapy history event shown in the detailed display mode in Colabrativ’s Clinical Entry and Operations (Cleo) application. All of the personal information displayed in this figure is fictitious, and does not represent a real individual or their medical history.

Other History Events Supported

The other history events that Colabrativ’s Clinical Entry and Operations (Cleo) application support are shown below.

Colabrativ’s Role in Small-Angle X-ray Scattering Experiments

Colabrativ’s role in this work started at the conceptual level during discussions with the Biogen Idec scientists about structural approaches to compare the FVIII and rFVIIIFc proteins. Crystallization was an obvious choice, but due to the flexible linker between the FVIII and the Fc in rFVIIIFc, crystallization of the rFVIIIFc was considered to have a low probability of success. SAXS had it own challenges, i.e. obtaining aggregate free samples of both proteins at reasonable concentrations. Early on while evaluating SAXS as an analysis option, we contacted Dr. John Tainer, who put us in touch with Dr. Susan Tsutakawa at SIBYLS beamline 12.3.1 at the Advanced Light Source (ALS). We made the contractual arrangements with the ALS and worked with the Biogen Idec staff to prepare and submit a successful SAXS proposal. We worked with both the Biogen Idec and ALS staffs on the preparation and shipping of the protein to the ALS. Working with Dr. Tsutakawa, we purified both proteins at the ALS by size-exclusion chromatography, prepared in a range of concentrations, and collected the SAXS data on the samples and their corresponding filtrates all in the same day.

Analysis of Factor VIII and Factor VIII-Fc SAXS Data

The analysis of the SAXS data and model refinement was performed by Dr. Tsutakawa beginning with initial models supplied by Biogen Idec.

The Guinier plots of the SAXS data for FVIII and rFVIIIFc showed both samples to be monodisperse; i.e. they have linear Guinier plot slopes. The radii of gyration (Rg) for FVIII and rFVIIIFc from the Guinier plots are 38Å and 51Å, respectively. The Electron Pair Distributions have a Dmax of 125Å and 175Å for FVIII and rFVIIIFc, respectively.

Models of FVIII and rFVIIIFc used the crystallographic structures of Factor VIII (3CDZ.pdb) and Fc as starting models. The program BILBOMD was used to identify a small set of conformations for these starting coordinates that best match the experimental SAXS data. Missing loops and carbohydrate chains were added to improve the fit to the SAXS data. For FVIII, the Chi value improved from 3.5 to 1.8 after modeling the missing loops and optimizing the conformation with BILBOMD, and to 1.5 after modeling the missing carbohydrate structures; see Figure 1.

Figure 1
Modeling of the FVIII Structure in Solution

The molecular dynamics simulation program BILBOMD was used to model conformers of BDD FVIII and compare their theoretical X-ray scattering curves to experimental scattering data. Three models are shown: The crystal structure of BDD FVIII (3CDZ.pdb – Chi=3.5), BDD FVIII with loops (Chi=1.8), and BDD FVIII with addition of N-linked carbohydrate (Chi=1.5). The fit of the three FVIII models to the experimental SAXS data is shown in the left panel.

The rFVIIIFc BILBOMD model has two conformations contributing to the best fit of SAXS data when only the missing loops were added. Unlike the FVIII modeling, the fit to the SAXS data did not improve when the carbohydrate structures were modeled and optimized with BILBOMD; see Figure 2.

Figure 2
Modeling of the rFVIIIFc Structure in Solution

BILBOMD was used to generate a minimal ensemble of structures for which theoretical X-ray scattering curves optimally fit experimental scattering data. Two models are shown: The rFVIIIFc model based on the BDD and Fc crystal structures with surface loops but lacking N glycans has a (Chi=1.5), and the same model with of N-linked carbohydrate present (Chi=1.6). The fit of the two rFVIIIFc models to the experimental SAXS data is shown in the upper-left panel.

Conclusion

The Fc domain in rFVIIIFc extends away from the regions in FVIII that are essential for interaction with elements of the Xase complex (anionic phospholipids, Factor IXa, and Factor X) and von Willebrand factor. This result is consistent with the conclusions from the H/DX study that shows that the fusion of Fc to FVIII does not perturb the structure of either the FVIII or Fc elements of rFVIIIFc.

Cleo is the result of a close collaboration between Clearity and Colabrativ. The project was under the direction of Dr. Deborah Zajchowski, The Clearity Foundation’s Scientific Director. The goal of the project was to move Clearity’s operations from Microsoft’s Access to an enterprise system. The project has two phases. The first phase was to migrate patient, physician, specimen data and test results from Access to Cleo. As of today, this has been accomplished. In the second phase we will be migrating patient medical histories from Access to Cleo.

Analysis of a patient’s test results is performed by a third party application on a second server. The Clearity staff use Cleo to initialize analysis requests and archive data that was sent for analysis. Cleo sends the patient information to the analysis server in a de-identified form (removal of information from the data that could be used to identify an individual). The analysis is then compiled by the Clearity staff into a report that is sent to the patient and their physician. The report highlights clinical treatment options based on the patient’s tumor molecular profile that is generated from the test results.

If you are interested in learning more about Cleo, please contact us at Colabrativ, Inc.

Patient Information Entry

Our initial focus is on entry of patient information and test results by the foundation staff, with the initial goal of automating the process as much as possible. The forms in the application are organized as tabs; see Figure 1. The tabs are organized to match the work flow of entering and analyzing patient information and test results.

Figure 1
People Tab in the Application

People tab in The Clearity Foundation application. All of the personal information displayed in this figure is fictitious and does not represent real individuals.

Figure 2
Specimens Tab in The Clearity Foundation Application

Specimens tab in The Clearity Foundation application. All of the personal information displayed in this figure is fictitious and does not represent real individuals or their specimens.

Figure 3
Results Tab in The Clearity Foundation Application

Results tab in The Clearity Foundation application. At the top, the Add (upload) section and one of the “Test-Lab” test set have been opened. In the open test set one of the IHC results is being edited. All of the personal information displayed in this figure is fictitious and does not represent real individuals or their results.

Changes to iExperiment an Enterprise Electronic Notebook

The following changes have been made to version 1.1 of iExperiment Enterprise Electronic Notebook (ELN):

• The options for viewing records under the Select tab have been changed. There are now four “List of Records I Can” options: read, edit, delete and download.
  

  Figure 1
  New View Record Options under Select Tab

  Top of Select tab in iExperiment showing the four new “List of Records I Can” options: read, edit, delete and download. The read option has been selected.

• Copy Record, Download Record Archive and Download PDF Archive buttons have been added to the tops of records.
  

  Figure 2
  New Copy Record, Download Record Archive and Download PDF Archive Buttons

  New Copy Record, Download Record Archive and Download PDF Archive buttons at the top of a record in iExperiment.

• Sponsoring Institution options have been added to the experiment properties file. The options are:
  • admin: Where the sponsored institution will be the primary administrator (institution key = 1).
  • author: Where the institution of the author’s active research period will be used.
  • key=: The sponsoring institution key will be identified by its database key; Example key=23

  In this AMI the sponsoring institution option is “admin”.

• Bug Fix: The material Oracle was failing to add materials that lacked a lot or serial number.
• Bug Fix: Sections containing no text, such as a Summary section with only the material produced, were not being displayed from a record archive in a web browser, despite being contained in the record archive.

Evaluating iExperiment an Enterprise Electronic Notebook

It’s easy for you to evaluate iExperiment through Amazon Web Services. A three-part tutorial is available, under the Free Trial tab in the navigation bar above, to guide you through i) the creation of an Amazon Elastic Compute Cloud instance using the iExperiment AMI, ii) configuration of iExperiment, and iii) adding your first researcher.

Browser Compatibility of iExperiment

iExperiment is built on Google Web Toolkit and is not compatible with all browsers. Currently, iExperiment works with Mozilla’s FireFox and Google’s Chrome, but does not work with Microsoft’s Internet Explorer or Apple’s Safari. Both Safari and Internet Explorer suffer from the same two problems:

1. The text editor fails to maintain preexisting text.
2. The file drag-and-drop capability introduces characters into the file names in Safari, and does not work at all in Internet Explorer.