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Predicting New Target Conditions for Drug Retesting Using Temporal Patterns in Clinical Trials: A Proof of Concept.

He Z, Weng C - AMIA Jt Summits Transl Sci Proc (2015)

Bottom Line: Efficient drug repurposing promises to accelerate drug discovery with reduced cost.However, most successful repurposing cases so far have been achieved by serendipity.There is a need for more efficient computational methods for predicting new indications for existing drugs.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Informatics, Columbia University, New York, NY.

ABSTRACT
Drug discovery is costly and time-consuming. Efficient drug repurposing promises to accelerate drug discovery with reduced cost. However, most successful repurposing cases so far have been achieved by serendipity. There is a need for more efficient computational methods for predicting new indications for existing drugs. This paper conducts a retrospective analysis of the temporal patterns of drug intervention trials for every drug in a pair of different conditions in ClinicalTrials.gov, including 550 drugs used for 451 conditions between 2003 and 2013. We found that drugs are often targeted towards conditions that are related by similar or identical eligibility criteria. We demonstrated the preliminary feasibility of predicting new target conditions for drug retesting among conditions with similar aggregated clinical trial eligibility criteria and confirmed this hypothesis using evidence from the literature.

No MeSH data available.


The numbers of different conditions that the top 20 most retested drugs were retested on.
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f2-2085703: The numbers of different conditions that the top 20 most retested drugs were retested on.

Mentions: Figure 2 displays the count of different conditions that a drug was retested on each year for the top 20 drugs that were retested on most conditions between 2004 and 2013. Each color block represents the number of different conditions that the drug was retested on compared to the previous year(s). The most retested drug (i.e., Bevacizumab) resides at the bottom of the figure. Note that since our time window is from 2003 to 2013, the first year that a drug could be retested for another condition is 2004. Most retested drugs were used in chemotherapeutic activities. One reason could be that chemotherapy usually uses multiple drugs to kill or control tumor cells. Meanwhile, chemotherapy drugs are often used to treat different types of neoplasms and cancers.


Predicting New Target Conditions for Drug Retesting Using Temporal Patterns in Clinical Trials: A Proof of Concept.

He Z, Weng C - AMIA Jt Summits Transl Sci Proc (2015)

The numbers of different conditions that the top 20 most retested drugs were retested on.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4525223&req=5

f2-2085703: The numbers of different conditions that the top 20 most retested drugs were retested on.
Mentions: Figure 2 displays the count of different conditions that a drug was retested on each year for the top 20 drugs that were retested on most conditions between 2004 and 2013. Each color block represents the number of different conditions that the drug was retested on compared to the previous year(s). The most retested drug (i.e., Bevacizumab) resides at the bottom of the figure. Note that since our time window is from 2003 to 2013, the first year that a drug could be retested for another condition is 2004. Most retested drugs were used in chemotherapeutic activities. One reason could be that chemotherapy usually uses multiple drugs to kill or control tumor cells. Meanwhile, chemotherapy drugs are often used to treat different types of neoplasms and cancers.

Bottom Line: Efficient drug repurposing promises to accelerate drug discovery with reduced cost.However, most successful repurposing cases so far have been achieved by serendipity.There is a need for more efficient computational methods for predicting new indications for existing drugs.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Informatics, Columbia University, New York, NY.

ABSTRACT
Drug discovery is costly and time-consuming. Efficient drug repurposing promises to accelerate drug discovery with reduced cost. However, most successful repurposing cases so far have been achieved by serendipity. There is a need for more efficient computational methods for predicting new indications for existing drugs. This paper conducts a retrospective analysis of the temporal patterns of drug intervention trials for every drug in a pair of different conditions in ClinicalTrials.gov, including 550 drugs used for 451 conditions between 2003 and 2013. We found that drugs are often targeted towards conditions that are related by similar or identical eligibility criteria. We demonstrated the preliminary feasibility of predicting new target conditions for drug retesting among conditions with similar aggregated clinical trial eligibility criteria and confirmed this hypothesis using evidence from the literature.

No MeSH data available.