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Conference Paper/Proceeding/Abstract 11664 views 112 downloads

Modelling and Forecasting Pharmaceutical Life Cycles

Sam Buxton Orcid Logo, Kostas Nikolopoulos, Marwan Khammash, Philip Stern

Swansea University Author: Sam Buxton Orcid Logo

Abstract

We examine the pharmaceutical sales in the context of lifecycle modelling and forecasting using time series analysis. This is accomplished by comparing the lifecycles of 1000 pharmaceutical drugs using an algorithm that determines the most common lifecycles of pharmaceutical drugs. The data regardin...

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Published: 2011
URI: https://cronfa.swan.ac.uk/Record/cronfa43658
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last_indexed 2018-10-22T13:22:51Z
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spelling 2018-10-22T12:10:10.8437265 v2 43658 2018-09-03 Modelling and Forecasting Pharmaceutical Life Cycles 27aacc6d5049c8d2c26495e4e6a6bd75 0000-0003-1007-7063 Sam Buxton Sam Buxton true false 2018-09-03 CBAE We examine the pharmaceutical sales in the context of lifecycle modelling and forecasting using time series analysis. This is accomplished by comparing the lifecycles of 1000 pharmaceutical drugs using an algorithm that determines the most common lifecycles of pharmaceutical drugs. The data regarding these drugs comes from a database known as Jigsaw that contains data associated with 2.57 million scripts written by General Practitioner’s (GP’s). Our research aims to produce these graphs for individual drugs using the number of sales that occurs, while also comparing the lifecycles for each drug in sixteen Regional Health Association’s (RHA’s). The second phase of the study focuses on forecasting the final section of the pharmaceutical drugs’ lifecycles using a number of state of the art methods to determine which accurately fits the data. Conference Paper/Proceeding/Abstract 27 6 2011 2011-06-27 COLLEGE NANME Management School COLLEGE CODE CBAE Swansea University 2018-10-22T12:10:10.8437265 2018-09-03T11:05:21.2585286 Faculty of Humanities and Social Sciences School of Management - Business Management Sam Buxton 0000-0003-1007-7063 1 Kostas Nikolopoulos 2 Marwan Khammash 3 Philip Stern 4 0043658-22102018120858.pdf IJFpresentation.pdf 2018-10-22T12:08:58.6000000 Output 305705 application/pdf Author's Original true 2018-10-22T00:00:00.0000000 true eng
title Modelling and Forecasting Pharmaceutical Life Cycles
spellingShingle Modelling and Forecasting Pharmaceutical Life Cycles
Sam Buxton
title_short Modelling and Forecasting Pharmaceutical Life Cycles
title_full Modelling and Forecasting Pharmaceutical Life Cycles
title_fullStr Modelling and Forecasting Pharmaceutical Life Cycles
title_full_unstemmed Modelling and Forecasting Pharmaceutical Life Cycles
title_sort Modelling and Forecasting Pharmaceutical Life Cycles
author_id_str_mv 27aacc6d5049c8d2c26495e4e6a6bd75
author_id_fullname_str_mv 27aacc6d5049c8d2c26495e4e6a6bd75_***_Sam Buxton
author Sam Buxton
author2 Sam Buxton
Kostas Nikolopoulos
Marwan Khammash
Philip Stern
format Conference Paper/Proceeding/Abstract
publishDate 2011
institution Swansea University
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management
document_store_str 1
active_str 0
description We examine the pharmaceutical sales in the context of lifecycle modelling and forecasting using time series analysis. This is accomplished by comparing the lifecycles of 1000 pharmaceutical drugs using an algorithm that determines the most common lifecycles of pharmaceutical drugs. The data regarding these drugs comes from a database known as Jigsaw that contains data associated with 2.57 million scripts written by General Practitioner’s (GP’s). Our research aims to produce these graphs for individual drugs using the number of sales that occurs, while also comparing the lifecycles for each drug in sixteen Regional Health Association’s (RHA’s). The second phase of the study focuses on forecasting the final section of the pharmaceutical drugs’ lifecycles using a number of state of the art methods to determine which accurately fits the data.
published_date 2011-06-27T01:44:52Z
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score 11.04748

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