RDI - Scientific Publications

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The core activity of the RDI is to elucidate the link between changes in the code of HIV, the genotype, and the response of the patient to different combinations of HIV drugs. New information about this relationship, and developments in our ability to mathematically model this relationship are of interest to the scientific, medical and HIV communities worldwide. We are, therefore, committed to the dissemination of our results, including via scientific presentation and publication.

Follow the links below to see abstracts from our publications as well as posters and slides from scientific conferences.

Computational models can accurately predict response to antiretroviral therapy without a genotype
B Larder ¹, D Wang ¹, A Revell ¹, R Harrigan ², J Gatell ³, L Ruiz ⁴, S Emery ⁵; C Torti ⁶, F DeWolf ⁷, A Pozniak ⁸, JM Montaner ² ¹ RDI, London, UK ² BC Centre for Excellence in HIV/AIDS, Vancouver, Canada ³ Hospital of Barcelona, Spain ⁴ Fundació irsiCaixa, Badalona, Spain ⁵ NCHECR, Sydney, Australia ⁶ University of Brescia, Brescia, Italy ⁷ Netherlands HIV Monitoring Foundation, Amsterdam, The Netherlands ⁸ Chelsea and Westminster Hospital, London, UK.	Abstract
Poster presentation at: 49th Infectious Diseases Medical Congress, Microbiology Medical Congress (ICAAC). San Francisco, USA.12th - 15th September 2009	Poster (623k)
A comparison of three computational modelling methods for the prediction of virological response to combination HIV therapy
Dechao Wang ¹, Brendan Larder ¹, Andrew Revell ¹, Julio Montaner ², Richard Harrigan ², Frank De Wolf ³, Joep Lange ⁴, Scott Wegner ⁵, Lidia Ruiz ⁶, María Jésus Pérez-Elías ⁷, Sean Emery ⁸, Jose Gatell ⁹, Antonella D’Arminio Monforte ¹⁰, Carlo Torti ¹¹, Maurizio Zazzi ¹², Clifford Lane ¹³ ¹ The HIV Resistance Response Database Initiative (RDI), London, UK ² BC Centre for Excellence in HIV/AIDS, Vancouver, Canada ³ Netherlands HIV Monitoring Foundation, Amsterdam, The Netherlands ⁴ Academic Medical Centre of the University of Amsterdam, Amsterdam, The Netherlands ⁵ Uniformed Services University of the Health Sciences, Bethesda, MD, USA ⁶ Fundacio´ irsiCaixa, Badalona, Spain ⁷ Ramo´n y Cajal Hospital, Madrid, Spain ⁸ National Centre in HIV Epidemiology and Clinical Research, Sydney, Australia ⁹ Hospital Clinic of Barcelona, Barcelona, Spain ¹⁰ University of Milan (on behalf of ICONA), Milan, Italy ¹¹ Institute for Infectious and Tropical Diseases, University of Brescia (on behalf of the Italian MASTER Cohort), Brescia, Italy ¹² University of Siena (on behalf of the Italian ARCA database), Siena, Italy ¹³ National Institute of Allergy and Infectious Diseases, Bethesda, MD, USA Original article published in: Artifical Intelligence in Medicine - Volume 47 No 1, September 2009	Article (447k)
Computational models developed without a genotype for resource-poor countries predict response to HIV treatment with 82% accuracy
AD Revell ¹, D Wang ¹, R Harrigan ², J Gatell ³, L Ruiz ⁴, S Emery ⁵, MJ Pérez-Elías ⁶, C Torti ⁷, J Baxter ⁸, F DeWolf ⁹, Brian Gazzard ¹⁰, AM Geretti ¹¹, S Staszewski ¹², R Hamers ¹³, AMJ Wensing ¹⁴, J Lange ¹⁵, JM Montaner ², BA Larder ¹ ¹ HIV Resistance Response Database Initiative (RDI), London, UK ² BC Centre for Excellence in HIV/AIDS, Vancouver, Canada ³ Hospital Clinic of Barcelona, Barcelona, Spain ⁴ Fundació irsiCaixa, Badalona, Spain ⁵ National Centre in HIV Epidemiology and Clinical Research, Sydney, Australia ⁶ Ramón y Cajal Hospital, Madrid, Spain ⁷ University of Brescia, Brescia, Italy ⁸ Cooper University Hospital, NJ, Camden, USA ⁹ Netherlands HIV Monitoring Foundation, Amsterdam, The Netherlands ¹⁰ Chelsea and Westminster Hospital, London, UK ¹¹ Royal Free Hospital, London, UK ¹² Hospital of the Johann Wolfgang Goethe-University, Frankfurt, Germany ¹³ PharmAccess Foundation, Academic Medical Centre, Amsterdam, The Netherlands ¹⁴ University Medical Centre, Utrecht, The Netherlands ¹⁵ Academic Medical Centre, Amsterdam, The Netherlands. Slide and Poster presentation at: XVIII International HIV Drug Resistance Workshop, Fort Myers, Florida, USA, 9-13 June 2009	Poster (661k) Slides (413k)
Application of artificial neural networks for decision support in medicine
Brendan Larder, Dechao Wang and Andy Revell HIV Resistance Response Database Initiative (RDI), London, UK Chapter published in: D.S. Livingstone (ed),(2008). Artificial Neural Networks: Methods and Applications. Humana Press (Springer- Verlag), New York.	Abstract
Preliminary Results of a Prospective Clinical Study of the RDI’s Computational Models as a Treatment Decision Tool
BA Larder ¹, D Wang ¹, AD Revell ¹, D Coe ¹, C Torti ², JSG Montaner ³, M Harris ³, HC Lane ⁴. ¹ HIV Resistance Response Database Initiative (RDI), London, UK ² University of Brescia, Brescia, Italy ³ BC Centre for Excellence in HIV/AIDS, Vancouver, Canada ⁴ National Institute of Allergy and Infectious Diseases (NIAID), Bethesda, MD, USA.	Abstract
Poster presentation at: XVII International HIV Drug Resistance Workshop, Sitges, Spain, 10-14 June 2008	Poster (1.16MB)
Development of computational models for prediction of virologic response in a prospective clinical study
BA Larder ¹, D Wang ¹, A Revell ¹, J Montaner ², R Harrigan ², S Wegner ³, HC Lane⁴. ¹ HIV Resistance Response Database Initiative (RDI), London, UK ² BC Centre for Excellence in HIV/AIDS, Vancouver, Canada ³ Uniformed Services University of the Health Sciences, Bethesda, MD, USA ⁴ National Institute of Allergy and Infectious Diseases (NIAID), Bethesda, MD, USA	Abstract
Poster presentation at: XVI International HIV Drug Resistance Workshop, Bridgetown, Barbados, 12-16 June 2007	Poster (645k)
The development of artificial neural networks to predict virological response to combination HIV therapy
Brendan Larder ¹, Dechao Wang ¹, Andrew Revell ¹, Julio Montaner ², Richard Harrigan ², Frank De Wolf ³, Joep Lange ⁴, Scott Wegner ⁵, Lidia Ruiz ⁶, María Jésus Pérez-Elías ⁷, Sean Emery ⁸, Jose Gatell ⁹, Antonella D‘Arminio Monforte ¹⁰, Carlo Torti ¹¹, Maurizio Zazzi ¹² and Clifford Lane ¹³ ¹ The HIV Resistance Response Database Initiative, London, UK ² BC Centre for Excellence in HIV/AIDS, Vancouver, Canada ³ Netherlands HIV Monitoring Foundation, Amsterdam, the Netherlands ⁴ Academic Medical Centre of the University of Amsterdam, Amsterdam, the Netherlands ⁵ Uniformed Services University of the Health Sciences, Bethesda, MD, USA ⁶ Fundació irsiCaixa, Badalona, Spain ⁷ Ramón y Cajal Hospital, Madrid, Spain ⁸ National Centre in HIV Epidemiology and Clinical Research, Sydney, Australia ⁹ Hospital Clinic of Barcelona, Barcelona, Spain ¹⁰ University of Milan, Milan Italy (on behalf of ICONA) ¹¹ Institute for Infectious and Tropical Diseases, University of Brescia, Brescia, Italy (on behalf of the Italian MASTER Cohort) ¹² University of Siena, Siena, Italy (on behalf of the Italian ARCA database) ¹³ National Institute of Allergy and Infectious Diseases, Bethesda, MD, USA	Abstract
Original article published in: Antiviral Therapy Volume 12 Year 2007 Issue 1	Link to journal
Accurate prediction of virologic response to HAART using three computational modelling techniques
BA Larder¹, D Wang¹, F De Wolf ², J Lange³, A Revell¹, S Wegner⁴, J Montaner⁵, R Harrigan⁵, JA Metcalf ⁶, HC Lane⁶. 1: RDI, London, UK; 2: Netherlands HIV Monitoring Foundation, Amsterdam, the Netherlands; 3: Academic Medical Centre of the University of Amsterdam, the Netherlands; 4: US Military HIV Research Program, Rockville, USA; 5: BC Centre for Excellence in HIV/AIDS, Vancouver, Canada; 6: National Institute of Allergy and Infectious Diseases (NIAID), Bethesda, MD, USA.	Abstract
Poster presentation at: XV International HIV Drug Resistance Workshop, Sitges, Spain, 13-17 June 2006.	Poster (943k)
Neural Networks Are More Accurate Predictors of Virologic Response to Antiretroviral Therapy Than Rules-Based Genotype Interpretation Systems
B.A. Larder¹, A.M. Geretti², L. Monno³, C Torti⁴, A. Revell¹, D. Wang¹, R. Harrigan⁵, J. Montaner^5, and H. C. Lane⁶. 1: RDI, London, UK; 2: Royal Free Hospital, London, UK; 3. University of Bari, Italy (on behalf of the PhenGen study); 4: University of Brescia, Italy; 5: BC Centre for Excellence in HIV/AIDS Vancouver, Canada; 6: NIAID, Bethesda, MD, USA.	Abstract
Poster presentation at: CROI 2006, Denver, CO, USA, 5-8 February 2006.	Poster (536k)
Treatment history but not previous genotype improves the accuracy of predicting virologic response to HIV therapy
B.A. Larder 1 , D. Wang 1 , A. Revell 1 , R. Harrigan 2 , J. Montaner 2 , S. Wegner 3 , and C. Lane 4 . 1: HIV Resistance Response Database Initiative, London, UK; 2: BC Centre for Excellence in HIV/AIDS Vancouver, Canada; 3: US Military HIV Research Program, Rockville, MD, USA; 4: National Institute of Allergy & Infectious Diseases, Bethesda, MD, USA.	Abstract
Poster presentation at: 45th ICAAC, Washington DC, USA, 16-19 December 2005.	Poster (536k)
Neural networks are more accurate predictors of virological response to HAART than rules-based genotype interpretation systems
B.A. Larder 1 , A. Revell 1 , D. Wang 1 , R. Harrigan 2 , J. Montaner 2 , S. Wegner 3 , and C. Lane 4 . 1: HIV Resistance Response Database Initiative, London, UK; 2: BC Centre for Excellence in HIV/AIDS Vancouver, Canada; 3: US Military HIV Research Program, Rockville, MD, USA; 4: National Institute of Allergy & Infectious Diseases, Bethesda, MD, USA.	Abstract
Poster presentation at: 10th European AIDS Conference/EACS, Dublin Ireland, 17-20 November 2005.	Poster (210k)
Treatment history improves the accuracy of neural networks predicting virologic response to HIV therapy
D. Wang 1 , B.A. Larder 1 , A. Revell 1 , R. Harrigan 2 , J. Montaner 2 , S. Wegner 3 , and C. Lane 4 1: HIV Resistance Response Database Initiative, London, UK; 2: BC Centre for Excellence in HIV/AIDS Vancouver, Canada; 3: US Military HIV Research Program, Rockville, MD, USA; 4: National Institute of Allergy & Infectious Diseases, Bethesda, MD, USA.	Abstract
Slide and Poster presentation at: BioSapiens-viRgil Workshop on Bioinformatics for Viral Infections 21-23 September 2005, Caesar Bonn, Germany.	Poster (231k) Slides (984k)
Global neural network models are superior to single clinic models as general quantitative predictors of virologic treatment response
A. Revell 1 , B.A. Larder 1 , D. Wang 1 , S. Wegner 2 , R. Harrigan 3 , J. Montaner 3 and C. Lane 4 1: The HIV Resistance Response Database Initiative (RDI), London, UK; 2: US Military HIV Research Program, Rockville, MD, USA; 3: The BC Centre for Excellence in HIV/AIDS Vancouver, BC, Canada; 4: National Institute of Allergy and Infectious Diseases (NIAID), Bethesda, MD, USA.	Abstract
Poster presentation at: 3rd IAS Conference on HIV Pathogenesis and Treatment 24-27 July 2005, Rio de Janeiro, Brazil.	Poster (333k)
Treatment history data significantly increase the accuracy of neural networks in predicting virological response to combination therapy
B.A. Larder 1 , D. Wang 1 , A. Revell 1 , R. Harrigan 2 , J. Montaner 2 , S. Wegner 3 , and C. Lane 4 . 1: The HIV Resistance Response Database Initiative (RDI), London , UK ; 2: The BC Centre for Excellence in HIV/AIDS Vancouver , BC , Canada ; 3: US Military HIV Research Program, Rockville , MD , USA ; 4: National Institute of Allergy and Infectious Diseases (NIAID), Bethesda , MD , USA .	Abstract
Poster presentation at: 3rd IAS Conference on HIV Pathogenesis and Treatment 24-27 July 2005, Rio de Janeiro, Brazil.	Poster (247k)
Addressing adherence improves the accuracy of neural networks' predictions of virologic treatment response.
J. Montaner 1 , B.A. Larder 2 , D. Wang 2 , A. Revell 2 , S. Wegner 3 , R. Harrigan 1 and C. Lane 4. 1: The BC Centre for Excellence in HIV/AIDS Vancouver, BC, Canada (BC-CfE); 2: The HIV Resistance Response Database Initiative (RDI), London, UK; 3: US Military HIV Research Program, Rockville, MD, USA; 4: National Institute of Allergy and Infectious Diseases (NIAID), Bethesda, MD, USA.	Abstract
Poster presentation at: 3rd IAS Conference on HIV Pathogenesis and Treatment 24-27 July 2005, Rio de Janeiro, Brazil.	Poster (262k)
Treatment History and Adherence Information Significantly Improves Prediction of Virological Response by Neural Networks
B.A. Larder 1 , D. Wang 1 , A. Revell 1 , R. Harrigan 2 , J. Montaner 2 , S. Wegner 3 , and C. Lane 4 . 1: The HIV Resistance Response Database Initiative (RDI), London, UK; 2: The BC Centre for Excellence in HIV/AIDS Vancouver, Canada; 3: US Military HIV Research Program, Rockville, USA; 4: National Institute of Allergy and Infectious Diseases (NIAID), Bethesda, USA.	Abstract
Poster presentation at: 14th International HIV Drug Resistance Workshop. Quebec, Canada; 7-11 June 2005	Poster (248k)
Global Neural Network Models Are Superior to Single Clinic Models as General Quantitative Predictors of Virologic Treatment Response
S. Wegner 1 , B.A. Larder 2 , D. Wang 2 , A. Revell 2 , R. Harrigan 3 , J. Montaner 3 and C. Lane 4 . 1: US Military HIV Research Program, Rockville, MD, USA; 2: RDI, London, UK; 3: The BC Centre for Excellence in HIV/AIDS Vancouver, BC, Canada; 4: National Institute of Allergy and Infectious Diseases (NIAID), Bethesda, MD, USA.	Abstract
Poster presentation at: XIV International HIV Drug Resistance Workshop. Quebec, Canada; 7-11 June 2005	Poster (218k)
Previous Drug Exposure Data Significantly Increase the Accuracy of Artificial Neural Networks in Predicting Virological Response to Combination Therapy
B.A. Larder 1 , D Wang 1 , A Revell 2 , R Harrigan 3 , J Montaner 3 and C. Lane 4 . 1: The HIV Resistance Response Database Initiative (RDI), Cambridge , UK ; 2: RDI Ltd, London , UK ; 3: The BC Centre for Excellence in HIV/AIDS Vancouver , Canada ; 4: National Institute of Allergy and Infectious Diseases (NIAID), Bethesda , USA .	Abstract
Poster presentation at: 13th International Drug Resistance Workshop Costa Adeje - Tenerife Sur, Canary Islands, Spain; June 8-12, 2004	Poster (220k)
Accuracy of Neural Network Models in Predicting HIV Treatment Response from Genotype May Depend on Diversity as well as Size of Data Sets
B.A. Larder 1 , D Wang 1 , A Revell 2 , R Harrigan 3 , J Montaner 3 and C. Lane 4 . 1: The HIV Resistance Response Database Initiative (RDI), Cambridge, UK; 2: RDI Ltd, London, UK; 3: The BC Centre for Excellence in HIV/AIDS Vancouver, Canada; 4: National Institute of Allergy and Infectious Diseases (NIAID), Bethesda, USA.	Abstract
Poster presentation at: The 11th Conference on Retroviruses and Opportunistic Infections San Francisco, CA, USA; 8-11 February 2004	Poster (202k)
Neural network model identified potentially effective drug combinations for patients failing salvage therapy
B.A. Larder 1, D Wang 1, A Revell 2 and C. Lane 3. 1: The HIV Resistance Response Database Initiative (RDI), Cambridge, UK; 2: RDI, London, UK; 3: National Institute of Allergy and Infectious Diseases, Bethesda, USA.	Abstract
Poster presentation at: 2nd IAS Conference on HIV Pathogenesis and Treatment Paris, France; 13-16 July 2003	Poster (154k)
Artificial intelligence identifies effective drugs for HIV patients whose treatment is failing
D. Wang, B.A. Larder, A. Revell, R. Harrigan, J. Montaner. On behalf of the HIV Resistance Response Database Initiative (RDI).	Abstract
Poster presentation at: 12th International Workshop on HIV Drug Resistance Cabo, Mexico; 10-13 June 2003	Poster (135k)
HIV Drug Resistance Testing: Current Practice and Future Direction
Brendan A. Larder PhD. Chair of the RDI Scientific Core Group, Cambridge, UK
Oral presentation at: Whistler HIV Update 2003 Whistler, BC, Canada; March 29-31, 2003	Abstract
A Collaborative HIV Resistance Response Database Initiative: Predicting Virological Failure Using Neural Network Models
D. Wang & B.A. Larder. On Behalf of The HIV Resistance Response Database Initiative (RDI)	Abstract
Poster presentation at: 4th International Congress on Drug Therapy in HIV Infection Glasgow, UK; 17-21 November 2002	Poster (146k)
The International HIV Resistance Response Database Initiative: A New Global Collaborative Approach to Relating Viral Genotype and Treatment to Clinical Outcome.
B.A. Larder, V.DeGruttola, S. Hammer, R. Harrigan, S. Wegner, D. Winslow & M. Zazzi. On behalf of the HIV Resistance Response Database Initiative (RDI)	Abstract
Oral presentation at: The XI International HIV Drug Resistance Workshop Seville, Spain; 2-5 July 2002	Slides (1.29Mb) (431k)
A Collaborative HIV Resistance Response Database Initiative: Predicting Virological Response Using Neural Network Models
D Wang, V.DeGruttola, S. Hammer, R. Harrigan, B. Larder, S. Wegner, D. Winslow & M. Zazzi. On Behalf of The HIV Resistance Response Database Initiative (RDI)	Abstract
Poster presentation at: The XI International HIV Drug Resistance Workshop Seville, Spain; 2-5 July 2002	Poster (132k)

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