Author Interviews, Gastrointestinal Disease, Pharmaceutical Companies / 15.08.2018
Crohn’s Disease: Positive Findings from Phase III Study of Antibiotic Combination
MedicalResearch.com Interview with:
Mr. Gilead Raday, MPhil, MSc
Chief Operating Officer
RedHill Biopharma Ltd
MedicalResearch.com: What is the background for this study? Would you briefly explain what is meant by Crohn's disease? How common is it and whom does it affect?
Response: Crohn's disease (CD) is a chronic, relapsing inflammatory gastrointestinal disorder characterized by a variety of symptoms, including severe abdominal pain, diarrhea, bleeding, bowel obstruction, fever and weight loss. The underlying cause of Crohn's is unknown; however, CD is believed to arise secondary to genetic and environmental stimuli. More than 1.5 million people suffer from CD globally and it is prevalent in the U.S., affecting more than 200 people per 100,000.
The current standard of care for Crohn's disease is limited to anti-inflammatories, immuno-suppressants and biologics that treat auto-immune disorders. These therapies target symptomatic improvement in the inflammation associated with CD, are widely considered to be of limited efficacy in the long term, and are associated with numerous side effects. This speaks to the great unmet need for an effective therapy for this debilitating disease.
Additionally, there is no current therapy that treats the suspected underlying cause of Crohn’s disease. We have developed RHB-104 with the MAP hypothesis in mind, which posits that Crohn's disease is caused by infection by a bacteria, Mycobacterium avium subspecies paratuberculosis (MAP). This is similar to peptic ulcer disease, a condition that was initially associated with stress, smoking, NSAIDs and other behavioral factors, yet was found to be caused by H. pylori bacterial infection in the 1980s, revolutionizing the field of ulcer treatment. Validation of this theory would revolutionize how Crohn's disease is viewed and treated by the medical community and RHB-104 is the only therapy in development targeting MAP infection.
Mr. Gilead Raday, MPhil, MSc
Chief Operating Officer
RedHill Biopharma Ltd
MedicalResearch.com: What is the background for this study? Would you briefly explain what is meant by Crohn's disease? How common is it and whom does it affect?
Response: Crohn's disease (CD) is a chronic, relapsing inflammatory gastrointestinal disorder characterized by a variety of symptoms, including severe abdominal pain, diarrhea, bleeding, bowel obstruction, fever and weight loss. The underlying cause of Crohn's is unknown; however, CD is believed to arise secondary to genetic and environmental stimuli. More than 1.5 million people suffer from CD globally and it is prevalent in the U.S., affecting more than 200 people per 100,000.
The current standard of care for Crohn's disease is limited to anti-inflammatories, immuno-suppressants and biologics that treat auto-immune disorders. These therapies target symptomatic improvement in the inflammation associated with CD, are widely considered to be of limited efficacy in the long term, and are associated with numerous side effects. This speaks to the great unmet need for an effective therapy for this debilitating disease.
Additionally, there is no current therapy that treats the suspected underlying cause of Crohn’s disease. We have developed RHB-104 with the MAP hypothesis in mind, which posits that Crohn's disease is caused by infection by a bacteria, Mycobacterium avium subspecies paratuberculosis (MAP). This is similar to peptic ulcer disease, a condition that was initially associated with stress, smoking, NSAIDs and other behavioral factors, yet was found to be caused by H. pylori bacterial infection in the 1980s, revolutionizing the field of ulcer treatment. Validation of this theory would revolutionize how Crohn's disease is viewed and treated by the medical community and RHB-104 is the only therapy in development targeting MAP infection. 
![MedicalResearch.com Interview with: Dr. Theodore Satterthwaite MD Assistant professor in the department of Psychiatry, and Cedric Xia, a MD-PhD candidate Perelman School of Medicine at the University of Pennsylvania MedicalResearch.com: What is the background for this study? What are the main findings? Response: Unlike other branches of modern medicine, psychiatry still solely replies on patient reports and physician observations for clinical decision-making. Without biologically-based tests, the diagnostic categories for mental health do not carve nature at its joint. This is evident in the high levels of co-morbidity across disorders and heterogeneity within disorders. Through this research, we studied a large sample of adolescents who completed MRI-based functional imaging, and used recently-developed machine learning techniques to uncover specific abnormalities that are highly predictive of a wide variety of psychiatric symptoms. Essentially, we tried to find brain patterns that were predictive of different types of psychiatric symptoms. We discovered four such brain-guided dimensions of psychopathology: mood, psychosis, fear, and disruptive behavior. While each of these dimensions exhibits a unique pattern of brain connectivity, a common feature of brain anomaly is shared across the dimensions. Notably, in all linked dimensions, the default mode network and fronto-parietal network, two brain regions that usually become increasingly distinct as the brain matures, were abnormally connected. This loss of normal brain network segregation supports the hypothesis that many psychiatric illnesses may be disorders of brain development. MedicalResearch.com: What should readers take away from your report? Response: This study shows that we can start to use the brain to guide our understanding of psychiatric disorders in a way that’s fundamentally different than grouping symptoms into clinical diagnostic categories. By moving away from clinical labels developed decades ago, we can begin to let the biology speak for itself. Our ultimate hope is that understanding the biology of mental illnesses will allow us to develop better treatments for our patients. MedicalResearch.com: What recommendations do you have for future research as a result of this work? Response: This study demonstrates the importance of incorporating vast amounts of biological data to study mental illness across clinical diagnostic boundaries. Moving forward, we hope to integrate genomic data in order to describe pathways from genes to brain to symptoms, which could ultimately be the basis for novel treatments for mental illness. MedicalResearch.com: Is there anything else you would like to add? Response: Future breakthroughs in brain science to understand mental illness requires large amount of data. While the current study takes advantage of one of the largest samples of youth, the size (n=999) remains dwarfed by the complexity of the brain. The neuroscience community is actively working towards collecting higher quality data in even larger samples, so we can validate and build upon the findings. Citation: Cedric Huchuan Xia, Zongming Ma, Rastko Ciric, Shi Gu, Richard F. Betzel, Antonia N. Kaczkurkin, Monica E. Calkins, Philip A. Cook, Angel García de la Garza, Simon N. Vandekar, Zaixu Cui, Tyler M. Moore, David R. Roalf, Kosha Ruparel, Daniel H. Wolf, Christos Davatzikos, Ruben C. Gur, Raquel E. Gur, Russell T. Shinohara, Danielle S. Bassett, Theodore D. Satterthwaite. Linked dimensions of psychopathology and connectivity in functional brain networks. Nature Communications, 2018; 9 (1) DOI: 10.1038/s41467-018-05317-y [wysija_form id="3"] [last-modified] The information on MedicalResearch.com is provided for educational purposes only, and is in no way intended to diagnose, cure, or treat any medical or other condition. Always seek the advice of your physician or other qualified health and ask your doctor any questions you may have regarding a medical condition. In addition to all other limitations and disclaimers in this agreement, service provider and its third party providers disclaim any liability or loss in connection with the content provided on this website.](https://medicalresearch.com/wp-content/uploads/Cross-clinical-diagnostic-categories.jpg)
![MedicalResearch.com Interview with: Dr. Theodore Satterthwaite MD Assistant professor in the department of Psychiatry, and Cedric Xia, a MD-PhD candidate Perelman School of Medicine at the University of Pennsylvania MedicalResearch.com: What is the background for this study? What are the main findings? Response: Unlike other branches of modern medicine, psychiatry still solely replies on patient reports and physician observations for clinical decision-making. Without biologically-based tests, the diagnostic categories for mental health do not carve nature at its joint. This is evident in the high levels of co-morbidity across disorders and heterogeneity within disorders. Through this research, we studied a large sample of adolescents who completed MRI-based functional imaging, and used recently-developed machine learning techniques to uncover specific abnormalities that are highly predictive of a wide variety of psychiatric symptoms. Essentially, we tried to find brain patterns that were predictive of different types of psychiatric symptoms. We discovered four such brain-guided dimensions of psychopathology: mood, psychosis, fear, and disruptive behavior. While each of these dimensions exhibits a unique pattern of brain connectivity, a common feature of brain anomaly is shared across the dimensions. Notably, in all linked dimensions, the default mode network and fronto-parietal network, two brain regions that usually become increasingly distinct as the brain matures, were abnormally connected. This loss of normal brain network segregation supports the hypothesis that many psychiatric illnesses may be disorders of brain development. MedicalResearch.com: What should readers take away from your report? Response: This study shows that we can start to use the brain to guide our understanding of psychiatric disorders in a way that’s fundamentally different than grouping symptoms into clinical diagnostic categories. By moving away from clinical labels developed decades ago, we can begin to let the biology speak for itself. Our ultimate hope is that understanding the biology of mental illnesses will allow us to develop better treatments for our patients. MedicalResearch.com: What recommendations do you have for future research as a result of this work? Response: This study demonstrates the importance of incorporating vast amounts of biological data to study mental illness across clinical diagnostic boundaries. Moving forward, we hope to integrate genomic data in order to describe pathways from genes to brain to symptoms, which could ultimately be the basis for novel treatments for mental illness. MedicalResearch.com: Is there anything else you would like to add? Response: Future breakthroughs in brain science to understand mental illness requires large amount of data. While the current study takes advantage of one of the largest samples of youth, the size (n=999) remains dwarfed by the complexity of the brain. The neuroscience community is actively working towards collecting higher quality data in even larger samples, so we can validate and build upon the findings. Citation: Cedric Huchuan Xia, Zongming Ma, Rastko Ciric, Shi Gu, Richard F. Betzel, Antonia N. Kaczkurkin, Monica E. Calkins, Philip A. Cook, Angel García de la Garza, Simon N. Vandekar, Zaixu Cui, Tyler M. Moore, David R. Roalf, Kosha Ruparel, Daniel H. Wolf, Christos Davatzikos, Ruben C. Gur, Raquel E. Gur, Russell T. Shinohara, Danielle S. Bassett, Theodore D. Satterthwaite. Linked dimensions of psychopathology and connectivity in functional brain networks. Nature Communications, 2018; 9 (1) DOI: 10.1038/s41467-018-05317-y [wysija_form id="3"] [last-modified] The information on MedicalResearch.com is provided for educational purposes only, and is in no way intended to diagnose, cure, or treat any medical or other condition. Always seek the advice of your physician or other qualified health and ask your doctor any questions you may have regarding a medical condition. In addition to all other limitations and disclaimers in this agreement, service provider and its third party providers disclaim any liability or loss in connection with the content provided on this website.](https://medicalresearch.com/wp-content/uploads/Cross-clinical-diagnostic-categories-200x180.jpg)
