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Department of Information Sciences

Joyce Niland, Ph.D.
Chair & Professor
626-256-HOPE (4673), ext. 63032
Fax: 626-301-8802
 
The Department of Information Sciences (DIS), consisting of the Divisions of Biostatistics, Research Informatics, Clinical Research Information Support, and Mathematical Oncology, collaborates in numerous facets of both clinical and basic science research throughout the Medical Center and Beckman Research Institute, including study design, data quality and training,and computational statistical analysis.
 
Major activities include collaborations in clinical, laboratory, and epidemiological research; development of statistical methodologies; and teaching in the Irell & Manella Graduate School of Biological Sciences and in the Clinical Investigation Training Program (CITP); development of innovative information systems for research. The faculty members within the department participate as co-investigators on City of Hope grants, in addition to conducting their own research.
 
Our Vision
To convert raw data into information leading to new knowledge, to help speed biomedical discoveries, disease prevention, and therapeutic interventions.
 
Our Mission
To contribute to City of Hope’s mission and strategic plan through the development and application of research information science methods and technologies, by:
 
  • Supporting information management, integration, and synthesis across the translational research pipeline
  • Collaborating in the design, computerization, analysis and reporting of basic, translational, clinical, and population research
  • Facilitating the collection and delivery of accurate, complete electronic data for disease registries
  • Ensuring high quality results by applying best practices and international standards
     
Division of Biostatistics
 
The Division of Biostatistics houses faculty and staff statisticians. Their major activities include: collaboration in basic, translational and clinical research; consulting on statistical questions in research; development of statistical methodology, teaching in the Irell & Manella Graduate School of Biological Sciences and in the Clinical Investigation Training Program. The division operates City of Hope's comprehensive cancer center's Biostatistics Core , and supports coordinating centers for the National Comprehensive Cancer Network, The NCRR Islet Cell Resource Centers and the California Cancer Consortium.

Division of Clinical Research Information Support

The Division of Clinical Research Information Support (CRIS) provides expertise in training and continuing education of clinical research staff, data quality assurance, data collection for observational databases, quality assurance, multi-center coordination for treatment and observational protocols, data collection for disease registries and transplant procedures at City of Hope, cancer registry, data entry, and Clinical Trials OnlineSM(CTOL). The Division operates the protocol data management component of the Cancer Center’s Clinical Protocol & Data Management (CPDM).
 
Division of Research Informatics

The Division of Research Informatics (RI) includes systems analysts, application developers/software engineers, database administrators/architects, Electronic Data Capture/TeleForms group, and decision support services. The staff within RI is specially trained to focus on the information systems requirements unique to the research domain. RI combines the administrative and clinical care data collected during the normal course of patient care with protocol-specific data collected for research purposes and makes it available for use in outcome assessment and analysis. The Division also operates the clinical research informatics component of the Cancer Center’s Clinical Protocol & Data Management (CPDM).
 
Through the Biostatistics Core and Clinical Protocol & Data Management Shared Resource, DIS faculty and staff follow NCI guidelines to provide support to Cancer Center members and City of Hope investigators.
 
Division of Mathematical Oncology 
 
Mathematical Oncology is the science of oncology that uses mathematics as the means of discovery. The goal of the Division of Mathematical Oncology is to translate mathematics, physics and evolution-based research to clinical care.

The scientific challenge of Mathematical Oncology is how best to use models to quantify and predict which patients are most likely to benefit from specific mono or combination therapies, using data that can be obtained in the clinic. Although prognostic classifiers such as recursive partitioning analysis provide a patient-specific prediction of overall survival, this and similar statistical methods do not account for the evolution and heterogeneity of the cancer before, during, and after treatment. Viewing cancer as a dynamic system perturbed by therapy and the body’s immune system is crucial to understanding the disease course and how to tailor treatments to individual disease.
 
 

Division of Biostatistics

Jeffrey Longmate, Ph.D.
Director
 
The Division of Biostatistics provides statistical expertise for basic, translational, and clinical research.
 
The services provided by the Division of Biostatistics are collaboration, consulting, and statistical computing. The core faculty members maintain expertise in a variety of specialized areas including clinical trials, high throughput functional genomics, pharmacokinetic modeling, epidemiology and statistical genetics.
 
The Division of Biostatistics assists Cancer Center and Beckman Research Institute investigators with study design, analytic plan development, database design and data extraction, efficacy and safety monitoring, manuscript preparation, and the development of grant proposals and clinical protocols. Service to the institution includes statistical review of cancer-related clinical research protocols for the CPRMC, IRB and DSMB. Outside of their core activities, the faculty members are also engaged in externally funded biomedical research, the development of statistical methodology and teaching in the graduate school and the Clinical Investigation Training Program.

The Biostatistics Core is directed by Jeffrey Longmate, Ph.D., Director of the Division of Biostatistics, with David D. Smith, Ph.D., serving as co-director. The Biostatistics Core draws effort from a large part of the Division of Biostatistics, with the Biostatistics Core enabling their participation in Cancer Center-related pilot projects and proposals, which may later develop into externally funded projects. The Biostatistics Core is directly involved in Cancer Center research from the inception of a research idea to the publication of results. Clinical research projects account for the largest portion of core use, but the Biostatistics Core also supports basic and translational research, as well as assisting several other cores. The Biostatistics Core staff collaborate closely with the Biomedical Informatics core to support data processing and analysis of gene expression microarrays, and the Biostatistics Core works closely with both the Clinical Research Informatics Core and the Clinical Trials Management Core to implement City of Hope-conducted or coordinated clinical protocols. In addition to these ongoing collaborative efforts, there have been more technically-focused projects in which the Biostatistics Core has supported the other cores in the implementation of technologies that involve statistical measurement issues.
 
 
  • Joyce Niland’s research interests are clinical trials methodology, outcomes research, and biomedical informatics. She also directs the Data Coordinating Centers for two nationwide research networks: (1) the National Comprehensive Cancer Network (NCCN) Outcomes Research Study, studying patterns of care, guideline concordance, and factors associated with patient outcomes within our nation’s Cancer Centers; and (2) the Islet Cell Resources (ICR) consortium, investigating optimization of islet cell harvesting for transplantation in type I diabetes.
  • Jeffrey Longmate’s research interests are study design and statistical inference arising from collaborations in genetics, immunology, and early-phase clinical trials. Dr. Longmate co-directs the coordinating center for multi-center Phase I/II drug development, directs the Data Coordinating Center for the Southern California Islet-Cell Consortium, and coordinates the Biostatistics segment of the Biostatistics and Bioinformatics course for the Graduate School and the Medical Fellows Training Program.
  • Li Cheng’s research interests include the role of genetic markers and receptors in the etiology and manifestation of disease processes.
  • David Smith is interested in pre-clinical study design, clinical trial methodology, and microarray study design and data analysis.
  • Paul Frankel’s research interests include clinical trials methodology and survival analysis techniques.
  • Rebecca Nelson’s research interests include exploring patterns of disease risk and outcomes as related to clinical and environmental covariates.
  • Dajun Qian’s research interests include clinical trial methodology, linkage analysis, and haplotype sharing correlation analysis.
  • Rebecca Ottesen
  • Joycelynne Palmer
  • Nora Ruel
  • Carolyn Behrendt
  • Suzette M. Blanchard
  • Min Sierra Li
  • Xueli Liu
  • F. Lennie Wong
  • Andy Dagis
  • Julie Kilburn
  • Arthur Li
  • Christopher Ruel
  • Tracey Stiller
  • Leanne Streja
  • Nicole Tsai
  • Wei Ye
 
 
 
 

Division of Clinical Research Information Support (CRIS)

Adina Londrc, M.D.
Director
alondrc@coh.org
626-256-HOPE (4673) Ext. 65553
Fax: 626-301-8965

 
Clinical Research Information Support (CRIS) provides centralized standardized support to City of Hope clinical research investigators and staff, including support to the Clinical Trials Unit (CTU) staff, as well as Clinical Research Coordinators (CRCs) collecting observational data. CRIS delivers resources and training, and develops programs and processes to establish best practices in accordance with Good Clinical Practice (GCP).

The division is dedicated to fostering an environment that enables clinical research to be conducted with the highest standards of quality, integrity and efficiency, working in close collaboration with Biostatistics and Research Informatics, to provide seamless services for your clinical research studies.CRIS also operates the protocol data management section of the Cancer Center's Clinical Protocol & Data Management (CPDM) shared resource.
 
The following services are offered to clinical research staff and investigators:
 
 
  • Curate and quality assure protocol data
  • Bookmark and load all PDF documents for protocols, consents & standard research orders
  • Post protocol alerts within 1-2 hours of request
  • Register your protocols to ClinicalTrials.gov and the NCI Clinical Trials Reporting Program
 
Data Quality
 
  • Case Report Form (CRF) design
  • Quality control of CRF data for in-house treatment and observational studies
  • Assistance with external audit data preparation
  • Data management preparation for FACT accreditation
     
Disease Registries
 
  • Data collection for observational disease registries
  • Data collection for hematology retrospective protocols
  • State mandated abstracting and reporting to the California Cancer Registry
  • Federally mandated data collection and reporting for all transplants performed at City of Hope
     
Multi-center Coordination
 
  • Multi-center coordination and support of both interventional and observational studies sponsored by City of Hope
  • Data coordinating center for NCI-sponsored trials through California Cancer Consortium-Pittsburg (CCC-P) and other externally peer-reviewed grants

 

 
 
 
 
 
 
 
 
 
 
 

Division of Mathematical Oncology

Russell Rockne, Ph.D.
Director
 
Mathematical Oncology is the science of oncology that uses mathematics as the means of discovery. The goal of the Division of Mathematical Oncology is to translate mathematics, physics and evolution-based research to clinical care.
 
The scientific challenge of Mathematical Oncology is how best to use models to quantify and predict which patients are most likely to benefit from specific mono or combination therapies, using data that can be obtained in the clinic. Although prognostic classifiers such as recursive partitioning analysis provide a patient-specific prediction of overall survival, this and similar statistical methods do not account for the evolution and heterogeneity of the cancer before, during, and after treatment. Viewing cancer as a dynamic system perturbed by therapy and the body’s immune system is crucial to understanding the disease course and how to tailor treatments to individual disease.
 
We believe Mathematical Oncology is methodological innovation that has the potential to change clinical trial design to incorporate tumor phenotype into patient selection and improve our understanding of differential responses between patients and further maximize benefit from therapies. This can be achieved with quantitative measures of tumor phenotype and response to therapy that can be used to compare patients with different therapies but similar phenotype to infer a differential benefit of therapy.
 

Division of Research Informatics

Ajay Shah, Ph.D.
Director
626-256-HOPE (4673), ext. 81967 
 
 
The Division of Research Informatics (RI) includes systems analysts, application developers/ software engineers, database administrators/architects, EDC/InTelescans group, and decision support services. The staff within RI is specially trained to focus on the information systems requirements unique to the research domain. RI combines the administrative and clinical care data collected during the normal course of patient care with protocol-specific data collected for research purposes and makes it available for use in outcome assessment and analysis.

The Division consists of three functional sections that include Clinical Research Informatics (CRI), Research Informatics Applications (RIA) and Translational Research Informatics (TRI). It also operates the Cancer Center’s Research Informatics section of the Clinical Protocol & Data Management (CPDM).
 
Research Informatics Applications
 
Srinivas Bolisetty
Director

Research Informatics Applications(RIA) seeks to employ emergent technologies and industry best practices to create integrated products that support the translational continuum. By taking an agile driven methodology, we are able to rapidly move requirements through a continuous integration pipeline - favoring frequent releases to minimize the time it takes for ideas to progress from concept to implementation while maximizing tolerance to change.

Services

  • Integrated Research Informatics Platform
  • In-house Applications
  • External Applications
  • Analysis, development, and integration of research support applications
  • Rapid Prototyping
  • Web & Mobile Development
     
In-House Applications
 
External Applications
 
 
Clinical Research Informatics (CRI)
 
Clinical Research Informatics (CRI) enables the effective and efficient execution of clinical research -- including clinical trials and outcomes research – by applying the science of information management. The key strategic goal of CRI is to build a world-class clinical research informatics infrastructure by implementing best-in-class vendor solutions where available and developing innovative solutions that give City of Hope researchers a competitive advantage. To advance this goal,CRI led the selection and implementation of the best-in-class Electronic Data Capture (EDC) solution for clinical trials with the Medidata EDC, and deployed the Clinical Research Portal business intelligence solution to help clinical researchers translate their data into decisions.
 
Services
 
  • Clinical Trials Data Capture and Management - Provide informatics solutions to manage the planning, execution, and reporting of clinical trials, such as protocol authoring, adverse event reporting, and subject enrollment
  • Observational Research Data Capture and Management - Provide electronic data capture (EDC) systems with electronic case report forms (eCRFs) or computer-scannable CRFs to capture study data, such as adverse events and tumor response
  • Clinical Research Decision Support - Transforms data into decisions using business intelligence tools to report and analyze study-related data
 
 
Translational Research Informatics Core (TRIC)
 
Translational Research Informatics (TRI) strives to empower ground breaking research from basic bench research to clinical research and back. Our goal is to provide contemporary technological solutions to nimbly and specifically support information capture, management and exchange across the Translational Research Space.
 
Our approach is to provide support and service at the individual lab level. Introducing new information technology solutions to help make gathering and visualization of experimental data more facile and at the same time, to optimize and make the process of scientific research more efficient. While our target clients are in the translational research space, we will develop, in time, an information infrastructure partnered with Clinical Research Informatics (CRI) and Bioinformatics that will spark and enable collaborations across basic and clinical research.
 
Services
 
  • Translational Research Experimental Data Capture, Management and Analyses
  • Systems and Process Analyses for Translational Research
  • Workflow/process analyses, optimization and automation.
  • Integrated inventory and sample management
 

Information Sciences Faculty and Staff

Information Sciences

Department of Information Sciences

Joyce Niland, Ph.D.
Chair & Professor
626-256-HOPE (4673), ext. 63032
Fax: 626-301-8802
 
The Department of Information Sciences (DIS), consisting of the Divisions of Biostatistics, Research Informatics, Clinical Research Information Support, and Mathematical Oncology, collaborates in numerous facets of both clinical and basic science research throughout the Medical Center and Beckman Research Institute, including study design, data quality and training,and computational statistical analysis.
 
Major activities include collaborations in clinical, laboratory, and epidemiological research; development of statistical methodologies; and teaching in the Irell & Manella Graduate School of Biological Sciences and in the Clinical Investigation Training Program (CITP); development of innovative information systems for research. The faculty members within the department participate as co-investigators on City of Hope grants, in addition to conducting their own research.
 
Our Vision
To convert raw data into information leading to new knowledge, to help speed biomedical discoveries, disease prevention, and therapeutic interventions.
 
Our Mission
To contribute to City of Hope’s mission and strategic plan through the development and application of research information science methods and technologies, by:
 
  • Supporting information management, integration, and synthesis across the translational research pipeline
  • Collaborating in the design, computerization, analysis and reporting of basic, translational, clinical, and population research
  • Facilitating the collection and delivery of accurate, complete electronic data for disease registries
  • Ensuring high quality results by applying best practices and international standards
     
Division of Biostatistics
 
The Division of Biostatistics houses faculty and staff statisticians. Their major activities include: collaboration in basic, translational and clinical research; consulting on statistical questions in research; development of statistical methodology, teaching in the Irell & Manella Graduate School of Biological Sciences and in the Clinical Investigation Training Program. The division operates City of Hope's comprehensive cancer center's Biostatistics Core , and supports coordinating centers for the National Comprehensive Cancer Network, The NCRR Islet Cell Resource Centers and the California Cancer Consortium.

Division of Clinical Research Information Support

The Division of Clinical Research Information Support (CRIS) provides expertise in training and continuing education of clinical research staff, data quality assurance, data collection for observational databases, quality assurance, multi-center coordination for treatment and observational protocols, data collection for disease registries and transplant procedures at City of Hope, cancer registry, data entry, and Clinical Trials OnlineSM(CTOL). The Division operates the protocol data management component of the Cancer Center’s Clinical Protocol & Data Management (CPDM).
 
Division of Research Informatics

The Division of Research Informatics (RI) includes systems analysts, application developers/software engineers, database administrators/architects, Electronic Data Capture/TeleForms group, and decision support services. The staff within RI is specially trained to focus on the information systems requirements unique to the research domain. RI combines the administrative and clinical care data collected during the normal course of patient care with protocol-specific data collected for research purposes and makes it available for use in outcome assessment and analysis. The Division also operates the clinical research informatics component of the Cancer Center’s Clinical Protocol & Data Management (CPDM).
 
Through the Biostatistics Core and Clinical Protocol & Data Management Shared Resource, DIS faculty and staff follow NCI guidelines to provide support to Cancer Center members and City of Hope investigators.
 
Division of Mathematical Oncology 
 
Mathematical Oncology is the science of oncology that uses mathematics as the means of discovery. The goal of the Division of Mathematical Oncology is to translate mathematics, physics and evolution-based research to clinical care.

The scientific challenge of Mathematical Oncology is how best to use models to quantify and predict which patients are most likely to benefit from specific mono or combination therapies, using data that can be obtained in the clinic. Although prognostic classifiers such as recursive partitioning analysis provide a patient-specific prediction of overall survival, this and similar statistical methods do not account for the evolution and heterogeneity of the cancer before, during, and after treatment. Viewing cancer as a dynamic system perturbed by therapy and the body’s immune system is crucial to understanding the disease course and how to tailor treatments to individual disease.
 
 

Biostatistics

Division of Biostatistics

Jeffrey Longmate, Ph.D.
Director
 
The Division of Biostatistics provides statistical expertise for basic, translational, and clinical research.
 
The services provided by the Division of Biostatistics are collaboration, consulting, and statistical computing. The core faculty members maintain expertise in a variety of specialized areas including clinical trials, high throughput functional genomics, pharmacokinetic modeling, epidemiology and statistical genetics.
 
The Division of Biostatistics assists Cancer Center and Beckman Research Institute investigators with study design, analytic plan development, database design and data extraction, efficacy and safety monitoring, manuscript preparation, and the development of grant proposals and clinical protocols. Service to the institution includes statistical review of cancer-related clinical research protocols for the CPRMC, IRB and DSMB. Outside of their core activities, the faculty members are also engaged in externally funded biomedical research, the development of statistical methodology and teaching in the graduate school and the Clinical Investigation Training Program.

The Biostatistics Core is directed by Jeffrey Longmate, Ph.D., Director of the Division of Biostatistics, with David D. Smith, Ph.D., serving as co-director. The Biostatistics Core draws effort from a large part of the Division of Biostatistics, with the Biostatistics Core enabling their participation in Cancer Center-related pilot projects and proposals, which may later develop into externally funded projects. The Biostatistics Core is directly involved in Cancer Center research from the inception of a research idea to the publication of results. Clinical research projects account for the largest portion of core use, but the Biostatistics Core also supports basic and translational research, as well as assisting several other cores. The Biostatistics Core staff collaborate closely with the Biomedical Informatics core to support data processing and analysis of gene expression microarrays, and the Biostatistics Core works closely with both the Clinical Research Informatics Core and the Clinical Trials Management Core to implement City of Hope-conducted or coordinated clinical protocols. In addition to these ongoing collaborative efforts, there have been more technically-focused projects in which the Biostatistics Core has supported the other cores in the implementation of technologies that involve statistical measurement issues.
 
 
  • Joyce Niland’s research interests are clinical trials methodology, outcomes research, and biomedical informatics. She also directs the Data Coordinating Centers for two nationwide research networks: (1) the National Comprehensive Cancer Network (NCCN) Outcomes Research Study, studying patterns of care, guideline concordance, and factors associated with patient outcomes within our nation’s Cancer Centers; and (2) the Islet Cell Resources (ICR) consortium, investigating optimization of islet cell harvesting for transplantation in type I diabetes.
  • Jeffrey Longmate’s research interests are study design and statistical inference arising from collaborations in genetics, immunology, and early-phase clinical trials. Dr. Longmate co-directs the coordinating center for multi-center Phase I/II drug development, directs the Data Coordinating Center for the Southern California Islet-Cell Consortium, and coordinates the Biostatistics segment of the Biostatistics and Bioinformatics course for the Graduate School and the Medical Fellows Training Program.
  • Li Cheng’s research interests include the role of genetic markers and receptors in the etiology and manifestation of disease processes.
  • David Smith is interested in pre-clinical study design, clinical trial methodology, and microarray study design and data analysis.
  • Paul Frankel’s research interests include clinical trials methodology and survival analysis techniques.
  • Rebecca Nelson’s research interests include exploring patterns of disease risk and outcomes as related to clinical and environmental covariates.
  • Dajun Qian’s research interests include clinical trial methodology, linkage analysis, and haplotype sharing correlation analysis.
  • Rebecca Ottesen
  • Joycelynne Palmer
  • Nora Ruel
  • Carolyn Behrendt
  • Suzette M. Blanchard
  • Min Sierra Li
  • Xueli Liu
  • F. Lennie Wong
  • Andy Dagis
  • Julie Kilburn
  • Arthur Li
  • Christopher Ruel
  • Tracey Stiller
  • Leanne Streja
  • Nicole Tsai
  • Wei Ye
 
 
 
 

Clinical Research Information Support

Division of Clinical Research Information Support (CRIS)

Adina Londrc, M.D.
Director
alondrc@coh.org
626-256-HOPE (4673) Ext. 65553
Fax: 626-301-8965

 
Clinical Research Information Support (CRIS) provides centralized standardized support to City of Hope clinical research investigators and staff, including support to the Clinical Trials Unit (CTU) staff, as well as Clinical Research Coordinators (CRCs) collecting observational data. CRIS delivers resources and training, and develops programs and processes to establish best practices in accordance with Good Clinical Practice (GCP).

The division is dedicated to fostering an environment that enables clinical research to be conducted with the highest standards of quality, integrity and efficiency, working in close collaboration with Biostatistics and Research Informatics, to provide seamless services for your clinical research studies.CRIS also operates the protocol data management section of the Cancer Center's Clinical Protocol & Data Management (CPDM) shared resource.
 
The following services are offered to clinical research staff and investigators:
 
 
  • Curate and quality assure protocol data
  • Bookmark and load all PDF documents for protocols, consents & standard research orders
  • Post protocol alerts within 1-2 hours of request
  • Register your protocols to ClinicalTrials.gov and the NCI Clinical Trials Reporting Program
 
Data Quality
 
  • Case Report Form (CRF) design
  • Quality control of CRF data for in-house treatment and observational studies
  • Assistance with external audit data preparation
  • Data management preparation for FACT accreditation
     
Disease Registries
 
  • Data collection for observational disease registries
  • Data collection for hematology retrospective protocols
  • State mandated abstracting and reporting to the California Cancer Registry
  • Federally mandated data collection and reporting for all transplants performed at City of Hope
     
Multi-center Coordination
 
  • Multi-center coordination and support of both interventional and observational studies sponsored by City of Hope
  • Data coordinating center for NCI-sponsored trials through California Cancer Consortium-Pittsburg (CCC-P) and other externally peer-reviewed grants

 

 
 
 
 
 
 
 
 
 
 
 

Mathematical Oncology

Division of Mathematical Oncology

Russell Rockne, Ph.D.
Director
 
Mathematical Oncology is the science of oncology that uses mathematics as the means of discovery. The goal of the Division of Mathematical Oncology is to translate mathematics, physics and evolution-based research to clinical care.
 
The scientific challenge of Mathematical Oncology is how best to use models to quantify and predict which patients are most likely to benefit from specific mono or combination therapies, using data that can be obtained in the clinic. Although prognostic classifiers such as recursive partitioning analysis provide a patient-specific prediction of overall survival, this and similar statistical methods do not account for the evolution and heterogeneity of the cancer before, during, and after treatment. Viewing cancer as a dynamic system perturbed by therapy and the body’s immune system is crucial to understanding the disease course and how to tailor treatments to individual disease.
 
We believe Mathematical Oncology is methodological innovation that has the potential to change clinical trial design to incorporate tumor phenotype into patient selection and improve our understanding of differential responses between patients and further maximize benefit from therapies. This can be achieved with quantitative measures of tumor phenotype and response to therapy that can be used to compare patients with different therapies but similar phenotype to infer a differential benefit of therapy.
 

Research Informatics

Division of Research Informatics

Ajay Shah, Ph.D.
Director
626-256-HOPE (4673), ext. 81967 
 
 
The Division of Research Informatics (RI) includes systems analysts, application developers/ software engineers, database administrators/architects, EDC/InTelescans group, and decision support services. The staff within RI is specially trained to focus on the information systems requirements unique to the research domain. RI combines the administrative and clinical care data collected during the normal course of patient care with protocol-specific data collected for research purposes and makes it available for use in outcome assessment and analysis.

The Division consists of three functional sections that include Clinical Research Informatics (CRI), Research Informatics Applications (RIA) and Translational Research Informatics (TRI). It also operates the Cancer Center’s Research Informatics section of the Clinical Protocol & Data Management (CPDM).
 
Research Informatics Applications
 
Srinivas Bolisetty
Director

Research Informatics Applications(RIA) seeks to employ emergent technologies and industry best practices to create integrated products that support the translational continuum. By taking an agile driven methodology, we are able to rapidly move requirements through a continuous integration pipeline - favoring frequent releases to minimize the time it takes for ideas to progress from concept to implementation while maximizing tolerance to change.

Services

  • Integrated Research Informatics Platform
  • In-house Applications
  • External Applications
  • Analysis, development, and integration of research support applications
  • Rapid Prototyping
  • Web & Mobile Development
     
In-House Applications
 
External Applications
 
 
Clinical Research Informatics (CRI)
 
Clinical Research Informatics (CRI) enables the effective and efficient execution of clinical research -- including clinical trials and outcomes research – by applying the science of information management. The key strategic goal of CRI is to build a world-class clinical research informatics infrastructure by implementing best-in-class vendor solutions where available and developing innovative solutions that give City of Hope researchers a competitive advantage. To advance this goal,CRI led the selection and implementation of the best-in-class Electronic Data Capture (EDC) solution for clinical trials with the Medidata EDC, and deployed the Clinical Research Portal business intelligence solution to help clinical researchers translate their data into decisions.
 
Services
 
  • Clinical Trials Data Capture and Management - Provide informatics solutions to manage the planning, execution, and reporting of clinical trials, such as protocol authoring, adverse event reporting, and subject enrollment
  • Observational Research Data Capture and Management - Provide electronic data capture (EDC) systems with electronic case report forms (eCRFs) or computer-scannable CRFs to capture study data, such as adverse events and tumor response
  • Clinical Research Decision Support - Transforms data into decisions using business intelligence tools to report and analyze study-related data
 
 
Translational Research Informatics Core (TRIC)
 
Translational Research Informatics (TRI) strives to empower ground breaking research from basic bench research to clinical research and back. Our goal is to provide contemporary technological solutions to nimbly and specifically support information capture, management and exchange across the Translational Research Space.
 
Our approach is to provide support and service at the individual lab level. Introducing new information technology solutions to help make gathering and visualization of experimental data more facile and at the same time, to optimize and make the process of scientific research more efficient. While our target clients are in the translational research space, we will develop, in time, an information infrastructure partnered with Clinical Research Informatics (CRI) and Bioinformatics that will spark and enable collaborations across basic and clinical research.
 
Services
 
  • Translational Research Experimental Data Capture, Management and Analyses
  • Systems and Process Analyses for Translational Research
  • Workflow/process analyses, optimization and automation.
  • Integrated inventory and sample management
 

Information Sciences Faculty and Staff

Information Sciences Faculty and Staff

Research Departments/Divisions

City of Hope is a leader in translational research - integrating basic science, clinical research and patient care.
 

Research Shared Services

City of Hope embodies the spirit of scientific collaboration by sharing services and core facilities with colleagues here and around the world.
 

Our Scientists

Our research laboratories are led by the best and brightest minds in scientific research.
 

City of Hope’s Irell & Manella Graduate School of Biological Sciences equips students with the skills and strategies to transform the future of modern medicine.
Learn more about City of Hope's institutional distinctions, breakthrough innovations and collaborations.
Support Our Research
By giving to City of Hope, you support breakthrough discoveries in laboratory research that translate into lifesaving treatments for patients with cancer and other serious diseases.
 
 
 
 


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  • There’s science camp, and then there’s “mystery” science camp. City of Hope’s new science camp for middle school students is of the especially engaging latter variety. From Monday, July 13, to Friday, July 17, rising middle-school students from across the San Gabriel Valley were presented with a “patient” with ...
  • Women diagnosed with breast cancer quickly learn their tumor’s type, meaning the characteristics that fuel its growth. That label guides the treatment of their disease, as well as their prognosis when it comes to treatment effectiveness. Sometimes, however, doctors can’t accurately predict treatment effectivene...
  • In years past, Bladder Cancer Awareness Month has been a sobering reminder of a disease with few treatment options. For patients with metastatic disease (disease that has spread from the bladder to distant organs), average survival is typically just over one year. Fortunately, things are changing. Academic inst...
  • Tina Wang was diagnosed with Stage 4 diffuse large b cell lymphoma at age 22. She first sought treatment at her local hospital, undergoing two cycles of treatment. When the treatment failed to eradicate her cancer, she came to City of Hope. Here, Wang underwent an autologous stem cell transplant and participate...