Artificial Intelligence and Cancer Drug Development

2021 ◽  
Vol 16 ◽  
Author(s):  
Fan Yang ◽  
Jerry D. Darsey ◽  
Anindya Ghosh ◽  
Hong-Yu Li ◽  
Mary Q. Yang ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Drug Development ◽  
De Novo ◽  
Drug Repositioning ◽  
De Novo Design ◽  
Cancer Drug ◽  
Target Validation ◽  
Cancer Drugs ◽  
Research Drug ◽  
Applications Of Ai

Background: The development of cancer drugs is among the most focused “bench to bedside activities” to improve human health. Because of the amount of data publicly available to cancer research, drug development for cancers has significantly benefited from big data and AI. In the meantime, challenges, like curating the data of low quality, remain to be resolved. Objective: This review focused on the recent advancements in and challenges of AI in developing cancer drugs. Method: We discussed target validation, drug repositioning, de novo design, and compounds' synthetic strategies. Results and Conclusion: AI can be applied to all stages during drug development, and some excellent reviews detailing the applications of AI in specific stages are available.

scholarly journals DRUG REPOSITION OF NON-CANCER DRUGS FOR CANCER TREATMENTS VIA PHARMACOVIGILANCE APPROACH - REPURPOSING DRUGS IN ONCOLOGY

2019 ◽  
pp. 310-314 ◽  
Author(s):  
Mrugank Bhaskarkumar Parmar ◽  
Shital Panchal
Keyword(s):  
Statistical Analysis ◽  
Cancer Treatment ◽  
Drug Repositioning ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Cancer Drug ◽  
Cancer Drugs ◽  
Management Activity ◽  
Post Marketing Surveillance ◽  
Source Data

This study for drug repositioning has been performed for the drugs which are in the market since more than a decade and they are approved with their well-established efficacy and safety in human being. Objective of this study was to reposition the existing non-cancer drug therapy for cancer treatment, which is having well characterized pharmacologic profile with more efficacy and least toxicity as anti-neoplastic agent. We have retrieved the source data from FDA Adverse Event Reporting System (FAERS) for the last 13 years covering duration from 2004 to 2016 and analysed those using pharmacovigilance approach ‘a proposed future novel pharmaceutical tool for drug reposition’. Signal management activity was performed for statistical analysis. Result of statistical analysis derived that propranolol; metformin; pioglitazone; dabigatran and nitroglycerin are the existing non-cancer drugs which deserved for their direct / indirect reposition for cancer treatment and anti-neoplastic activity. Further studies retrieving the source data from other regulatory database (e.g. Eudravigilance of EMA and VigiFlow of WHO) and post-marketing surveillance study with the same objective may adjuvant our results for the reposition of existing drugs by pharmacovigilance approach.

scholarly journals De Novo Design of Bioactive Small Molecules by Artificial Intelligence

2018 ◽  
Vol 37 (1-2) ◽  
pp. 1700153 ◽  
Author(s):  
Daniel Merk ◽  
Lukas Friedrich ◽  
Francesca Grisoni ◽  
Gisbert Schneider
Keyword(s):  
Artificial Intelligence ◽  
Small Molecules ◽  
De Novo ◽  
De Novo Design

scholarly journals Drug Repositioning: New Approaches and Future Prospects for Life-Debilitating Diseases and the COVID-19 Pandemic Outbreak

Viruses ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1058
Author(s):  
Zheng Yao Low ◽  
Isra Ahmad Farouk ◽  
Sunil Kumar Lal
Keyword(s):  
Drug Development ◽  
De Novo ◽  
Drug Repositioning ◽  
Personalised Medicine ◽  
Technological Advancement ◽  
The Novel ◽  
Ongoing Research ◽  
Alternative Approach ◽  
Good Potential ◽  
Novel Drug

Traditionally, drug discovery utilises a de novo design approach, which requires high cost and many years of drug development before it reaches the market. Novel drug development does not always account for orphan diseases, which have low demand and hence low-profit margins for drug developers. Recently, drug repositioning has gained recognition as an alternative approach that explores new avenues for pre-existing commercially approved or rejected drugs to treat diseases aside from the intended ones. Drug repositioning results in lower overall developmental expenses and risk assessments, as the efficacy and safety of the original drug have already been well accessed and approved by regulatory authorities. The greatest advantage of drug repositioning is that it breathes new life into the novel, rare, orphan, and resistant diseases, such as Cushing’s syndrome, HIV infection, and pandemic outbreaks such as COVID-19. Repositioning existing drugs such as Hydroxychloroquine, Remdesivir, Ivermectin and Baricitinib shows good potential for COVID-19 treatment. This can crucially aid in resolving outbreaks in urgent times of need. This review discusses the past success in drug repositioning, the current technological advancement in the field, drug repositioning for personalised medicine and the ongoing research on newly emerging drugs under consideration for the COVID-19 treatment.

scholarly journals De Novo Design of New Chemical Entities (NCEs) for SARS-CoV-2 Using Artificial Intelligence

2020 ◽  
Author(s):  
Navneet Bung ◽  
Sowmya Ramaswamy Krishnan ◽  
Gopalakrishnan Bulusu ◽  
Arijit Roy
Keyword(s):  
Artificial Intelligence ◽  
Small Molecules ◽  
De Novo ◽  
Chemical Space ◽  
De Novo Design ◽  
Protein Targets ◽  
Post Translational Modifications ◽  
Global Pandemic ◽  
New Chemical Entities ◽  
3Cl Protease

The novel SARS-CoV-2 is the source of a global pandemic COVID-19, which has severely affected the health and economy of several countries. Multiple studies are in progress, employing diverse approaches to design novel therapeutics against the potential target proteins in SARS-CoV-2. One of the well-studied protein targets for coronaviruses is the chymotrypsin-like (3CL) protease, responsible for post-translational modifications of viral polyproteins essential for its survival and replication in the host. There are ongoing attempts to repurpose the existing viral protease inhibitors against 3CL protease of SARS-CoV-2. Recent studies have proven the efficiency of artificial intelligence techniques in learning the known chemical space and generating novel small molecules. In this study, we employed deep neural network-based generative and predictive models for de novo design of new small molecules capable of inhibiting the 3CL protease. The generated small molecules were filtered and screened against the binding site of the 3CL protease structure of SARS-CoV-2. Based on the screening results and further analysis, we have identified 31 potential compounds as ideal candidates for further synthesis and testing against SARS-CoV-2. The generated small molecules were also compared with available natural products. Two of the generated small molecules showed high similarity to a plant natural product, Aurantiamide, which can be used for rapid testing during this time of crisis.

scholarly journals De Novo Design of New Chemical Entities (NCEs) for SARS-CoV-2 Using Artificial Intelligence

2020 ◽  
Author(s):  
Navneet Bung ◽  
Sowmya Ramaswamy Krishnan ◽  
Gopalakrishnan Bulusu ◽  
Arijit Roy
Keyword(s):  
Artificial Intelligence ◽  
Small Molecules ◽  
De Novo ◽  
Chemical Space ◽  
De Novo Design ◽  
Protein Targets ◽  
Post Translational Modifications ◽  
Global Pandemic ◽  
New Chemical Entities ◽  
3Cl Protease

The novel SARS-CoV-2 is the source of a global pandemic COVID-19, which has severely affected the health and economy of several countries. Multiple studies are in progress, employing diverse approaches to design novel therapeutics against the potential target proteins in SARS-CoV-2. One of the well-studied protein targets for coronaviruses is the chymotrypsin-like (3CL) protease, responsible for post-translational modifications of viral polyproteins essential for its survival and replication in the host. There are ongoing attempts to repurpose the existing viral protease inhibitors against 3CL protease of SARS-CoV-2. Recent studies have proven the efficiency of artificial intelligence techniques in learning the known chemical space and generating novel small molecules. In this study, we employed deep neural network-based generative and predictive models for de novo design of new small molecules capable of inhibiting the 3CL protease. The generated small molecules were filtered and screened against the binding site of the 3CL protease structure of SARS-CoV-2. Based on the screening results and further analysis, we have identified 31 potential compounds as ideal candidates for further synthesis and testing against SARS-CoV-2. The generated small molecules were also compared with available natural products. Two of the generated small molecules showed high similarity to a plant natural product, Aurantiamide, which can be used for rapid testing during this time of crisis.

Antidepressants and antipsychotic agents as repurposable oncological drug candidates

2020 ◽  
Vol 27 ◽  
Author(s):  
Michał Antoszczak ◽  
Anna Markowska ◽  
Janina Markowska ◽  
Adam Huczyński
Keyword(s):  
Drug Development ◽  
De Novo ◽  
Drug Repositioning ◽  
Drug Repurposing ◽  
Antipsychotic Agents ◽  
Therapeutic Action ◽  
Drug Candidates ◽  
New Strategy ◽  
The Central Nervous System ◽  
Medical Indications

: Drug repurposing, known also as drug repositioning/reprofiling, is a relatively new strategy for identification of alternative uses of well-known therapeutics that are outside the scope of their original medical indications. Such an approach might entail a number of advantages compared to standard de novo drug development, including less time needed to introduce the drug to the market, and lower costs. The group of compounds that could be considered as promising candidates for repurposing in oncology includes the central nervous system drugs, especially selected antidepressant and antipsychotic agents. In this article, we provide an overview of some antidepressants (citalopram, fluoxetine, paroxetine, sertraline) and antipsychotics (chlorpromazine, pimozide, thioridazine, trifluoperazine) that have the potential to be repurposed as novel chemotherapeutics in cancer treatment, as they have been found to exhibit preventive and/or therapeutic action in cancer patients. Nevertheless, although drug repurposing seems to be an attractive strategy to search for oncological drugs, we would like to clearly indicate that it should not replace the search for new lead structures, but only complement de novo drug development.

scholarly journals De Novo Design of New Chemical Entities (NCEs) for SARS-CoV-2 Using Artificial Intelligence

2020 ◽  
Author(s):  
Navneet Bung ◽  
Sowmya Ramaswamy Krishnan ◽  
Gopalakrishnan Bulusu ◽  
Arijit Roy
Keyword(s):  
Artificial Intelligence ◽  
Small Molecules ◽  
De Novo ◽  
Chemical Space ◽  
De Novo Design ◽  
Protein Targets ◽  
Post Translational Modifications ◽  
Global Pandemic ◽  
New Chemical Entities ◽  
3Cl Protease

The novel SARS-CoV-2 is the source of a global pandemic COVID-19, which has severely affected the health and economy of several countries. Multiple studies are in progress, employing diverse approaches to design novel therapeutics against the potential target proteins in SARS-CoV-2. One of the well-studied protein targets for coronaviruses is the chymotrypsin-like (3CL) protease, responsible for post-translational modifications of viral<br>polyproteins essential for its survival and replication in the host. There are ongoing attempts to repurpose the existing viral protease inhibitors against 3CL protease of SARS-<br>CoV-2. Recent studies have proven the efficiency of artificial intelligence techniques in learning the known chemical space and generating novel small molecules. In this study,<br>we employed deep neural network-based generative and predictive models for de novo design of new small molecules capable of inhibiting the 3CL protease. The generated<br>small molecules were filtered and screened against the binding site of the 3CL protease structure of SARS-CoV-2. Based on the screening results and further analysis, we have<br>identified 31 potential compounds as ideal candidates for further synthesis and testing against SARS-CoV-2.

Sign in / Sign up

Export Citation Format

Share Document