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Report Description
Cancer is known to be one of the leading causes of death worldwide. In the US, 0.6 million deaths (https://www.cancer.gov/about-cancer/understanding/statistics) were reported to have been caused due to cancer in 2018 alone. Further, according to the International Agency for Research on Cancer (IARC), close to 17 million new cancer cases were reported in 2018, worldwide. By 2040, it is estimated that the aforementioned number is likely to grow to 27.5 million. It is worth mentioning that in the past five years, the United States Food and Drug Administration (USFDA) (https://www.fda.gov/drugs/resources-information-approved-drugs/hematologyoncology-cancer-approvals-safety-notifications) has approved more than 100 drugs for the treatment of different types of cancer. , However, as the growing global population is gradually being exposed to a growing list of risk factors and cancer causing agents, there is a pressing need for more specific and potent drugs / therapies to combat this complex, life threatening clinical condition. Over time, conventional treatment options, such as chemotherapy, surgery and radiation therapy, have shown limited efficacy in treating late-stage cancers. In addition, the non-specific and highly toxic nature of these therapies have severe detrimental effects on patients’ quality of life.
Defects in deoxyribonucleic acid (DNA) repair have been shown to be one of the primary causes of cancer. Moreover, tumor cells that are characterized by impaired DNA repair pathways typically become reliant on alternative DNA repair pathways for survival. This phenomenon is commonly referred to as oncogene addiction. Inhibitors of such compensatory repair pathways have the potential to sensitize cancer cells to DNA damaging agents and other therapeutic regimens. On the other hand, the simultaneous inactivation of certain pairs of genes have been shown to cause cell death. This phenomenon is known as synthetic lethality. In cancers, where mutations have led to the loss of function of one gene, using a drug molecule that specifically targets the corresponding gene of the synlet pair has been demonstrated to be a viable and effective therapeutic regimen. Recent advances in biomarker research, including the development of companion diagnostics, in combination with modern molecular screening platforms, which include clustered regularly interspaced short palindromic repeats (CRISPR)- and RNA interference (RNAi)-based screening techniques (https://www.ncbi.nlm.nih.gov/pubmed/28523286), have led to the identification of a number of synthetically lethal gene pairs. , ,
Currently, there are four approved (and marketed) poly-ADP ribose polymerase (PARP) inhibitor drugs, which have been shown to operate based on the concept of synthetic lethality. Further, several such drugs are being investigated for the treatment of a myriad of advanced oncological and non-oncological indications. A number of companies are engaged in this domain; moreover, both venture capital (VC) firms and government bodies are actively funding such research initiatives.
The ‘Synthetic Lethality-based Drugs and Targets Market, 2019-2030: Focus on DNA Repair (including PARP Inhibitors) and Other Novel Cellular Pathways’ report features an extensive study of the current market landscape and the future potential of the synthetic lethality-based therapeutics. It features an in-depth analysis, highlighting the capabilities of various companies engaged in this domain. In addition to other elements, the study includes:
One of the key objectives of the report was to estimate the existing market size and identify the future opportunity for synthetic lethality-based drugs, over the next decade. Based on multiple parameters, such as target consumer segments, region-specific disease prevalence, anticipated adoption of the marketed and late stage drugs and the likely selling price, we have provided informed estimates on the evolution of the market over the period 2019-2030. The report includes potential sales forecast of drugs that are currently marketed or are in late stages of development (phase II and above). The report also features the likely distribution of the current and forecasted opportunity across [A] type of molecules (small molecule and biologic), [B] different target indications (breast cancer, cervical / anogenital cancer, diabetic macular edema, gastric cancer, lung cancer, ovarian cancer and renal cell cancer), [C] synlet targets (APE1 / REF-1, CHK1, GLS1, PARP, Polθ, and WEE1), [D] route of administration (oral and intravenous), and [E] key geographical regions (North America, EU5, Asia-Pacific and Rest of the World). To account for the uncertainties associated with the growth of synthetic lethality-based drugs market and to add robustness to our model, we have provided three market forecast scenarios, namely conservative, base and optimistic scenarios, representing different tracks of the industry’s growth.
The opinions and insights presented in this study were also influenced by discussions conducted with multiple stakeholders in this domain. The report features detailed transcripts of interviews held with the following individuals (in alphabetical order of company names):
All actual figures have been sourced and analyzed from publicly available information forums and primary research discussions. Financial figures mentioned in this report are in USD, unless otherwise specified.
Contents
Chapter Outlines
Chapter 2 provides an executive summary of the insights captured during our research. It offers a high-level view on the current state of the synthetic lethality-based drugs market and its likely evolution in the short-mid term and long term.
Chapter 3 provides a general introduction to the DNA damage and associated repair systems in the human body. This section features a detailed discussion on the different types of DNA damage that have been identified so face, along with their respective causes. It also features detailed descriptions of DNA repair systems and associated biological pathways that are activated during upon the detection of damage within the cell’s genetic code. Further, the chapter includes a discussion on the potential therapeutic benefits of targeting defects in DNA repair pathways for the treatment of different disease indications, such as cancer.
Chapter 4 provides an overview of the concept of synthetic lethality, including details on the associated pathways and their respective mechanisms of action. Further, it includes a discussion on the conception, historical evolution, importance, applications and challenges related to the use of synthetic lethality as a therapeutic principle. The chapter also highlights the most popular types of screening approaches that are used in the identification of synlet gene pairs. Additionally, it includes an analysis of contemporary Google Trends (as of June 2019) and insights from recent news articles related to the concept of synthetic lethality.
Chapter 5 includes information on nearly 75 synthetic lethality-based drugs that are currently approved or under development for the treatment of various indications. It features a comprehensive analysis of pipeline molecules, highlighting phase of development (marketed, clinical, preclinical and discovery stage) of lead candidates, type of molecule (small molecule and biologic), type of therapy (monotherapy and combination therapy), type of synlet target, target patient segment, key therapeutic area(s) and target indication(s), and route of administration of the drugs that are being developed for the treatment of cancer. Further, the chapter provides information on drug developer(s), highlighting their year of establishment, location of headquarters and employee strength. In addition, the chapter highlights the various screening platforms that are being actively used by the industry to study synlet interactions between gene pairs.
Chapter 6 features detailed profiles of some of the large companies developing synthetic lethality-based drugs (shortlisted on the basis of phase of development of pipeline products). Each company profile includes a brief overview of the company, its financial information (if available), detailed descriptions of their synthetic lethality-based drugs, and a comprehensive future outlook. Additionally, each drug profile features information on type of drug, route of administration, indications, current status of development and an excerpt on its developmental history. In addition, the chapter includes tabulated profiles of small-sized and mid-sized players (shortlisted on the basis of the number of pipeline products), featuring details on the innovator company (such as location of headquarters, year of establishment, number of employees, and key members of executive team,) recent developments, along with descriptions of their synthetic lethality-based drug candidates.
Chapter 7 provides insights on the popularity of synthetic lethality on the social media platform, Twitter. The section highlights the yearly distribution of tweets, posted on the platform during the period 2010-2019 (till May), and the most significant events responsible for increase in the volume of tweets each year. Additionally, the chapter highlights the most prolific contributors, frequently discussed synlet targets, popular disease indications, and a multivariate tweet benchmark analysis in order to highlight the most popular tweets.
Chapter 8 provides a detailed analysis of close to 700 peer-reviewed scientific articles related to synthetic lethality, published during the period 2017-2019 (till May). The analysis takes into consideration target disease indications, synlet targets, and analysis based on various relevant parameters, such as study type (review article, research article and case report), research objective, year of publication, key research hubs, most popular authors, provision of grant support, and most popular journals (in terms of number of articles published in the given time period and journal impact factor). The chapter also features detailed valuation analysis for recent publications.
Chapter 9 features a detailed analysis of various abstracts related to synthetic lethality presented at ASCO in the period 2013-2019 (till May). The analysis is based on multiple parameters, such as year of (abstract) publication, popular drugs, synlet targets, target cancer indications, popular authors, author designations, industry type (industry and academia) and most active organizations (in terms of published abstracts). In addition, this chapter features a multi-dimensional bubble chart analysis to assess the relative level of expertise of the key authors / researchers based on number of publications, citation count and research gate score.
Chapter 10 provides information on close to 750 grants that were awarded to research institutes engaged in projects related to synthetic lethality, between 2014 and 2019 (till May). The analysis also highlights important parameters associated with grants, such as year of award, support period, amount awarded, funding institute, administration institute center, funding institute center, funding mechanism, spending categorization, grant type, responsible study section, focus area, type of recipient organization and prominent program officers. It also features a detailed analysis on most popular targets and target indications, along with a multivariate grant attractiveness analysis based on parameters; such as amount awarded, support period, grant type, number of synlet targets and number of indications under study.
Chapter 11 presents details on various investments received by start-ups / small-sized and mid-sized companies that are engaged in this domain. It also includes an analysis of the funding instances that have taken place in the market, in the period 2017-2019 (till May), highlighting the growing interest of the venture capital (VC) community and other strategic investors within this domain.
Chapter 12 presents benchmark analysis of over 230 synlet targets identified from various credible sources (research publications, government funding, clinical studies, recent news / tweets and abstracts presented in global conferences), highlighting targets that have already been validated in clinical studies, preclinical studies and early-stage research (cases where there is no lead (therapeutic) candidate being investigated). Further, it also highlights the long-term opportunities (for drug developers) associated with individual targets, based on their popularity across different portals.
Chapter 13 presents information on various companion diagnostics tests that are commercially available / being investigated for drugs that are designed to exploit the synthetic lethality mechanism. The chapter analyzes the innovative companion diagnostics on the basis of several parameters, such as the synlet target, drug candidate(s) being investigated, target biomarker(s), target disease indication(s) and assay technique used. It also includes case studies, highlighting those companion diagnostic tests that are available and are being used to evaluate the therapeutic efficiency of approved PARP inhibitors using the principle of synthetic lethality.
Chapter 14 features a detailed market forecast of the likely growth of synthetic lethality-based drugs till the year 2030. We have provided inputs on the likely distribution of the current and forecasted opportunity across type of molecules (small molecule and biologic), target indications (breast cancer, cervical / anogenital cancer, diabetic macular edema, gastric cancer, lung cancer, ovarian cancer and renal cell cancer), synlet targets (APE1 / REF-1, CHK1, GLS1, PARP, Polθ, and WEE1), different route of administration (oral and intravenous) and key geographical regions (North America, EU5, Asia-Pacific and Rest of the World). To account for future uncertainties associated with the growth of synthetic lethality-based drugs market and to add robustness to our model, we have provided three market forecast scenarios, namely conservative, base and optimistic scenarios, representing different tracks of the industry’s growth. .
Chapter 15 summarizes the entire report. It presents a list of key takeaways and offers our independent opinion on the current market scenario. Further, it captures the evolutionary trends that are likely to determine the future of synthetic lethality-based drugs market.
Chapter 16 is a collection of interview transcripts of discussions held with key stakeholders in this market. In this chapter, we have presented the details of interviews held with (in alphabetical order of company names) Simon Boulton (Vice President, Science Strategy, Artios Pharma), Yi Xu (Associate Director, Business Development, IMPACT Therapeutics), Norbert Perrimon (Professor, Department of Genetics, Harvard Medical School), Vivek Dharwal (Professor, Department of Biochemistry, Panjab University) and Alfred Nijkerk (Chief Executive Officer, UbiQ).
Chapter 17 is an appendix, which provides tabulated data and numbers for all the figures included in the report.
Chapter 18 is an appendix, which provides the list of companies and organizations mentioned in this report.
1. PREFACE
1.1. Scope of the Report
1.2. Research Methodology
1.3. Chapter Outlines
2. EXECUTIVE SUMMARY
3. INTRODUCTION TO DNA DAMAGE AND REPAIR SYSTEMS
3.1. Chapter Overview
3.2. Overview of Deoxyribonucleic Acid (DNA) Damage
3.3. DNA Damaging Agents
3.3.1. Endogenous DNA Damaging Agents
3.3.2. Exogenous DNA Damaging Agents
3.3.3. Other DNA Damaging Agents
3.4. DNA Damage Response System
3.4.1. Key Components of DNA Repair System
3.5. Types of DNA Repair Systems
3.5.1. Direct Repair
3.5.1.1. Photoreactivation
3.5.1.2. Alkyl Transferase Mediated Direct DNA Repair
3.5.1.3. AlkB Mediated Direct DNA Repair
3.5.1.4. DNA Ligase Mediated Direct DNA Repair
3.5.2. Excision Repair
3.5.2.1. Base Excision Repair (BER)
3.5.2.1.1. BER Pathway: Key Enzymes
3.5.2.1.1.1. DNA Glycosylases
3.5.2.1.1.2. Apurinic / Apyrimidinic (AP) Endonucleases
3.5.2.1.1.3. Other Enzymes
3.5.2.1.2. Short-Patch Base Excision Repair
3.5.2.1.3. Long-Patch Base Excision Repair
3.5.2.2. Nucleotide Excision Repair (NER)
3.5.2.3. Mismatch Repair
3.5.3. Indirect Repair
3.5.3.1. Homologous Recombination Repair (HRR)
3.5.3.2. Non-Homologous End-Joining
3.6. Mutations in DNA Repair Genes
4. INTRODUCTION TO SYNTHETIC LETHALITY
4.1. Chapter Overview
4.2. Concept of Synthetic Lethality
4.2.1. Historical Evolution of Synthetic Lethality
4.2.2. HRR and Synthetic Lethality
4.2.3. Other Synthetic Lethal Gene Interactions
4.2.4. Advantages of Synthetic Lethality
4.2.5. Limitations of Synthetic Lethality
4.3. Identification of Synlet Interactions
4.3.1. Hypothesis-Driven Approach
4.3.2. Screening-Based Approaches
4.3.2.1. Chemical Library-Based Screening Approaches
4.3.2.1.1. Non-Annotated Libraries
4.3.2.1.2. Annotated Libraries
4.3.2.2. Genome-Wide Interference-Based Screening Approaches
4.3.2.2.1. Ribonucleic Acid Interference (RNAi) Based Synlet Target Identification
4.3.2.2.2. Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) Based Synlet Target Identification
4.3.3. In Silico Approaches
4.4. Prevalent Trends Related to Synthetic Lethality
4.4.1. Recent News on Google: Emerging Focus Areas
4.4.2. Google Trends Analysis: Historical Timeline
4.4.3. Google Trends Analysis: Geographical Activity
4.4.4. Google Trends Analysis: Other Key Terms Related to Synthetic Lethality
4.5 Concluding Remarks
5. MARKET OVERVIEW
5.1. Chapter Overview
5.2. Synthetic Lethality-based Drugs: Marketed and Development Pipeline
5.2.1. Analysis by Phase of Development
5.2.2. Analysis by Type of Molecule
5.2.3. Analysis by Type of Therapy
5.2.4. Analysis by Type of Synlet Target
5.2.5. Analysis by Therapeutic Area
5.2.6. Analysis by Target Indication
5.2.7. Analysis by Patient Segment
5.2.8. Analysis by Route of Administration
5.3. Synthetic Lethality-based Drugs: List of Screening Platforms
5.4 Synthetic Lethality-based Drugs: List of Drug Developers / Screening Platform Providers
5.4.1. Analysis by Year of Establishment
5.4.2. Analysis by Location of Headquarters
5.4.3. Analysis by Company Size
5.4.4. Analysis by Company Size and Location of Headquarters
5.4.5. Leading Drug Developers
6. COMPANY PROFILES
6.1. Chapter Overview
6.2. Profiles of Established Players
6.2.1. AbbVie
6.2.1.1. Company Overview
6.2.1.2. Synthetic Lethality-based Drug Portfolio
6.2.1.2.1. Veliparib (ABT-888)
6.2.1.3. Recent Developments and Future Outlook
6.2.2. AstraZeneca
6.2.2.1. Company Overview
6.2.2.2. Synthetic Lethality-based Drug Portfolio
6.2.2.2.1. Olaparib (Lynparza®)
6.2.2.2.2. AZD6738
6.2.2.2.3. AZD1775
6.2.2.3. Recent Developments and Future Outlook
6.2.3. BeiGene
6.2.3.1. Company Overview
6.2.3.2. Synthetic Lethality-based Drug Portfolio
6.2.3.2.1. Pamiparib (BGB-290)
6.2.3.3. Recent Developments and Future Outlook
6.2.4. Clovis Oncology
6.2.4.1. Company Overview
6.2.4.2. Synthetic Lethality-based Drug Portfolio
6.2.4.2.1. Rucaparib (Rubraca®)
6.2.4.3. Recent Developments and Future Outlook
6.2.5. GlaxoSmithKline
6.2.5.1. Company Overview
6.2.5.2. Synthetic Lethality-based Drug Portfolio
6.2.5.2.1. Niraparib (Zejula®)
6.2.5.3. Recent Developments and Future Outlook
6.2.6. Pfizer
6.2.6.1. Company Overview
6.2.6.2. Synthetic Lethality-based Drug Portfolio
6.2.6.2.1. Talazoparib (TALZENNA®)
6.2.6.3. Recent Developments and Future Outlook
6.3. Profiles of Small and Mid-Sized Players
6.3.1. AtlasMedx
6.3.2. Chordia Therapeutics
6.3.3. IDEAYA Biosciences
6.3.4. Mission Therapeutics
6.3.5. Repare Therapeutics
6.3.6. Sierra Oncology
6.3.7. SyntheX Labs
7. EMERGING TRENDS ON SOCIAL MEDIA
7.1. Chapter Overview
7.2. Scope and Methodology
7.3. Synthetic Lethality: Trends on Twitter
7.3.1. Cumulative Year-Wise Activity
7.3.2. Historical Trends in Volume of Tweets
7.3.3. Evolutionary Trend Analysis
7.3.4. Trending Words / Phrases on Twitter
7.3.5. Most Prolific Contributors on Twitter
7.3.6. Most Popular Synlet Targets / Patient Mutations on Twitter
7.3.7. Most Popular Indications on Twitter
7.3.8. Heat Map Analysis: Distribution by Synlet Targets / Patient Mutations and Indications
7.4. Most Popular Tweets
7.5. Concluding Remarks
8. PUBLICATION ANALYSIS
8.1. Chapter Overview
8.2. Scope and Methodology
8.3. Synthetic Lethality: List of Recent Publications, 2019
8.3.1. Analysis by Type of Publication
8.3.2. Analysis by Study Objective
8.4. Synthetic Lethality: Publication Analysis, 2017–2019
8.4.1. Analysis by Year of Publication
8.4.2. Emerging Focus Areas
8.4.3. Analysis by Synlet Targets / Patient Mutations
8.4.3.1. Most Popular Synlet Targets / Patient Mutations
8.4.3.2. Year-Wise Trend in Activity for Popular Synlet Targets / Patient Mutations
8.4.4. Analysis by Target Indications
8.4.4.1. Most Popular Target Indications
8.4.4.2. Year-Wise Trend in Activity for Popular Target Indications
8.4.5. Analysis by Key Research Journals
8.4.5.1. Key Journals Based on Number of Publications
8.4.5.2. Analysis by Journal Impact Factor
8.4.5.3. Key Journals Based on Journal Impact Factor
8.4.6. Key Research Hubs
8.4.7. Most Popular Authors
8.4.8. Analysis of Publications with Grant Support
8.4.8.1. Most Popular Grant Bodies
8.4.8.2. Location of Grant Bodies
8.5. Publication Benchmark Analysis
9. ABSTRACT ANALYSIS
9.1. Chapter Overview
9.2. Scope and Methodology
9.3. Synthetic Lethality: List of American Society of Clinical Oncology Abstracts
9.3.1. Analysis by Year of Publication
9.3.2. Emerging Focus Areas
9.3.3. Most Popular Drugs
9.3.4. Most Popular Synlet Targets / Patient Mutations
9.3.5. Most Popular Target Indications
9.3.6. Most Popular Principal Authors
9.3.6.1. Analysis by Locations of Principal Authors
9.3.6.2. Analysis by Type of Organization of Principal Authors
9.3.6.3. Analysis by Active Organization
9.3.6.4. Analysis by Author Designation
9.3.6.5. Most Popular Authors
10. ACADEMIC GRANTS ANALYSIS
10.1. Chapter Overview
10.2. Scope and Methodology
10.3. Synthetic Lethality: List of Grants Awarded by National Institutes of Health
10.3.1. Analysis by Year of Award
10.3.2. Analysis by Amount Awarded
10.3.3. Analysis by Administering Institute Center
10.3.4. Analysis by Funding Institute Center
10.3.5. Analysis by Support Period
10.3.6. Analysis by Funding Institute Center and Support Period
10.3.7. Most Popular National Institute of Health (NIH) Funding Categorization
10.3.8. Analysis by Funding Mechanism
10.3.9. Analysis by Emerging Focus Areas
10.3.10. Most Popular Synlet Targets / Patient Mutations
10.3.11. Most Popular Target Indications
10.3.12. Analysis by Type of Grant Application
10.3.13. Most Popular NIH Departments
10.3.14. Analysis by Study Section
10.3.15. Analysis by Type of Recipient Organization
10.3.16. Most Popular Recipient Organization
10.3.17. Most Popular Recipient Organization and NIH Spending Sectors
10.3.18. Analysis by Grant Activity
10.3.19. Most Prominent Program Officers
10.3.20. Regional Distribution of Recipient Organization
10.4. Grant Attractiveness Analysis
11. FUNDING AND INVESTMENT ANALYSIS
11.1. Chapter Overview
11.2. Types of Funding
11.3. Synthetic Lethality: List of Funding and Investments
11.3.1. Analysis by Number of Instances
11.3.2. Analysis by Amount Invested
11.3.3. Analysis by Type of Funding
11.3.4. Analysis by Type of Company
11.3.5. Analysis by Purpose of Funding
11.3.6. Analysis by Type of Molecule
11.3.7. Analysis by Synlet Target
11.3.8. Analysis by Therapeutic Area
11.3.9. Analysis by Target Indication
11.3.10. Analysis by Geography
11.3.11. Most Active Players
11.3.12. Most Active Investors
11.4. Concluding Remarks
12. TARGET BENCHMARK ANALYSIS
12.1. Chapter Overview
12.2. Scope and Methodology
12.3. Target Benchmark Analysis
12.3.1. Clinically Validated Synlet Targets
12.3.2. Preclinically Validated Synlet Targets
12.3.3. Early Stage Research Validated Synlet Targets
12.4. Initiatives of Big Pharmaceutical Players
12.5. Concluding Remarks
13. ROLE OF COMPANION DIAGNOSTICS IN SYNTHETIC LETHALITY
13.1. Chapter Overview
13.2. Concept of Companion Diagnostics
13.3. Development of Companion Diagnostics
13.3.1. Co-development / Parallel Development Approach
13.3.2. Development of Companion Diagnostics Post Drug Approval
13.3.3. Development of already Approved Companion Diagnostics for New Drugs / Disease Indications
13.4. Advantages of Companion Diagnostics
13.5. Applications of Companion Diagnostics in Synthetic Lethality
13.6. Companion Diagnostics: List of Available / Under Development Tests
13.6.1. Analysis by Synlet Target
13.6.2. Analysis by Type of Biomarker
13.6.3. Analysis by Type of Biomarker and Technology
13.6.4. Analysis by Target Indication
13.6.5. Analysis by Developer and Synlet Target
13.6.6. Most Prominent Developers
13.7. Case-in-Point: Companion Diagnostics for Commercially Available Poly-ADP Ribose Polymerase (PARP) Inhibitors
13.7.1. Companion Diagnostics Test for Niraparib
13.7.1.1. Product Overview
13.7.1.2. Working Process
13.7.1.3. Collaborations
13.7.2. Companion Diagnostics Test for Olaparib
13.7.2.1. Product Overview
13.7.2.2. Working Process
13.7.2.3. Collaborations
13.7.3. Companion Diagnostics Test for Rucaparib
13.7.3.1. Product Overview
13.7.3.2. Collaborations
13.7.4. Companion Diagnostics Test for Talazoparib
13.7.4.1. Product Overview
13.7.4.2. Collaborations
13.8. Future Perspective
14. MARKET FORECAST
14.1. Chapter Overview
14.2. Scope and Limitations
14.3. Forecast Methodology and Key Assumptions
14.4. Overall Synthetic Lethality-based Drugs Market, 2019-2030
14.4.1. Synthetic Lethality-based Drugs Market: Distribution by Type of Molecule, 2019 and 2030
14.4.1.1. Synthetic Lethality-based Drugs Market for Small Molecule, 2019-2030
14.4.1.2. Synthetic Lethality-based Drugs Market for Biologic, 2019-2030
14.4.2. Synthetic Lethality-based Drugs Market: Distribution by Synlet Target, 2019 and 2030
14.4.2.1. Synthetic Lethality-based Drugs Market for APE1 / REF-1, 2019-2030
14.4.2.2. Synthetic Lethality-based Drugs Market for CHK1, 2019-2030
14.4.2.3. Synthetic Lethality-based Drugs Market for GLS1, 2019-2030
14.4.2.4. Synthetic Lethality-based Drugs Market for PARP, 2019-2030
14.4.2.5. Synthetic Lethality-based Drugs Market for Polθ, 2019-2030
14.4.2.6. Synthetic Lethality-based Drugs Market for WEE1, 2019-2030
14.4.3. Synthetic Lethality-based Drugs Market: Distribution by Target Indication, 2019 and 2030
14.4.3.1. Synthetic Lethality-based Drugs Market for Breast Cancer, 2019-2030
14.4.3.2. Synthetic Lethality-based Drugs Market for Cervical / Anogenital Cancer, 2019-2030
14.4.3.3. Synthetic Lethality-based Drugs Market for Diabetic Macular Edema, 2019-2030
14.4.3.4. Synthetic Lethality-based Drugs Market for Gastric Cancer, 2019-2030
14.4.3.5. Synthetic Lethality-based Drugs Market for Lung Cancer, 2019-2030
14.4.3.5. Synthetic Lethality-based Drugs Market for Ovarian Cancer, 2019-2030
14.4.3.7. Synthetic Lethality-based Drugs Market for Renal Cell Cancer, 2019-2030
14.4.4. Synthetic Lethality-based Drugs Market: Distribution by Route of Administration, 2019 and 2030
14.4.4.1. Synthetic Lethality-based Drugs Market for Oral Therapies, 2019-2030
14.4.4.2. Synthetic Lethality-based Drugs Market for Intravenous Therapies, 2019-2030
14.4.5. Synthetic Lethality-based Drugs Market: Distribution by Geography, 2019 and 2030
14.4.5.1. Synthetic Lethality-based Drugs Market in the US, 2019-2030
14.4.5.2. Synthetic Lethality-based Drugs Market in France, 2019-2030
14.4.5.3. Synthetic Lethality-based Drugs Market in Germany, 2019-2030
14.4.5.4. Synthetic Lethality-based Drugs Market in Italy, 2019-2030
14.4.5.5. Synthetic Lethality-based Drugs Market in Spain, 2019-2030
14.4.5.6. Synthetic Lethality-based Drugs Market in the UK, 2019-2030
14.4.5.8. Synthetic Lethality-based Drugs Market in Australia, 2019-2030
14.4.5.7. Synthetic Lethality-based Drugs Market in China, 2019-2030
14.4.5.8. Synthetic Lethality-based Drugs Market in Japan, 2019-2030
14.4.6. Product-wise Sales Forecast
14.4.6.1 Niraparib (GlaxoSmithKline)
14.4.6.1.1. Target Patient Population
14.4.6.1.2. Sales Forecast (USD Million)
14.4.6.1.3. Net Present Value (USD Million)
14.4.6.1.4. Value Creation Analysis
14.4.6.2. Olaparib (AstraZeneca)
14.4.6.2.1. Target Patient Population
14.4.6.2.2. Sales Forecast (USD Million)
14.4.6.2.3. Net Present Value (USD Million)
14.4.6.2.4. Value Creation Analysis
14.4.6.3. Rucaparib (Clovis Oncology)
14.4.6.3.1. Target Patient Population
14.4.6.3.2. Sales Forecast (USD Million)
14.4.6.3.3. Net Present Value (USD Million)
14.4.6.3.4. Value Creation Analysis
14.4.6.4. Talazoparib (Pfizer)
14.4.6.4.1. Target Patient Population
14.4.6.4.2. Sales Forecast (USD Million)
14.4.6.4.3. Net Present Value (USD Million)
14.4.6.4.4. Value Creation Analysis
14.4.6.5. Pamiparib (BeiGene)
14.4.6.5.1. Target Patient Population
14.4.6.5.2. Sales Forecast (USD Million)
14.4.6.5.3. Net Present Value (USD Million)
14.4.6.5.4. Value Creation Analysis
14.4.6.6. Veliparib (AbbVie)
14.4.6.6.1. Target Patient Population
14.4.6.6.2. Sales Forecast (USD Million)
14.4.6.6.3. Net Present Value (USD Million)
14.4.6.6.4. Value Creation Analysis
14.4.6.7. Adavosertib (AstraZeneca)
14.4.6.7.1. Target Patient Population
14.4.6.7.2. Sales Forecast (USD Million)
14.4.6.7.3. Net Present Value (USD Million)
14.4.6.7.4. Value Creation Analysis
14.4.6.8. APX3330 (Apexian Pharmaceuticals)
14.4.6.8.1. Target Patient Population
14.4.6.8.2. Sales Forecast (USD Million)
14.4.6.8.3. Net Present Value (USD Million)
14.4.6.8.4. Value Creation Analysis
14.4.6.9. CX-5461 (Senhwa Biosciences)
14.4.6.9.1. Target Patient Population
14.4.6.9.2. Sales Forecast (USD Million)
14.4.6.9.3. Net Present Value (USD Million)
14.4.6.9.4. Value Creation Analysis
14.4.6.10. SRA737-01 (Sierra Oncology)
14.4.6.10.1. Target Patient Population
14.4.6.10.2. Sales Forecast (USD Million)
14.4.6.10.3. Net Present Value (USD Million)
14.4.6.10.4. Value Creation Analysis
14.4.6.11. SRA737-02 (Sierra Oncology)
14.4.6.11.1. Target Patient Population
14.4.6.11.2. Sales Forecast (USD Million)
14.4.6.11.3. Net Present Value (USD Million)
14.4.6.11.4. Value Creation Analysis
14.4.6.12. Telaglenastat (Calithera Biosciences)
14.4.6.12.1. Target Patient Population
14.4.6.12.2. Sales Forecast (USD Million)
14.4.6.12.3. Net Present Value (USD Million)
14.4.6.12.4. Value Creation Analysis
14.4.7. Concluding Remarks
15. CONCLUDING REMARKS
16. EXECUTIVE INSIGHTS
16.1. Chapter Overview
16.2. Artios Pharma
16.2.1. Company / Organization Snapshot
16.2.2. Interview Transcript: Simon Boulton, Vice President, Science Strategy
16.3. IMPACT Therapeutics
16.3.1. Company / Organization Snapshot
16.3.2. Interview Transcript: Yi Xu, Associate Director
16.4. Harvard Medical School
16.4.1. Company / Organization Snapshot
16.4.2. Interview Transcript: Norbert Perrimon, Professor, Department of Genetics
16.5. Panjab University
16.5.1. Company / Organization Snapshot
16.5.2. Interview Transcript: Vivek Dharwal, Professor, Department of Biochemistry
16.6. UbiQ
16.6.1. Company / Organization Snapshot
16.6.2. Interview Transcript: Alfred Nijkerk, Chief Executive Officer
17. APPENDIX 1: TABULATED DATA
18. APPENDIX 2: LIST OF COMPANIES AND ORGANIZATIONS
Figure 3.1 Types of DNA Damage
Figure 3.2 Types of DNA Damaging Agents
Figure 3.3 DNA Damage and Repair Systems
Figure 3.4 DNA Damage Response Systems
Figure 3.5 Steps Involved in Base Excision Repair Pathway
Figure 3.6 Steps Involved in Nucleotide Excision Repair Pathway
Figure 3.7 Steps Involved in Mismatch Repair Pathway
Figure 3.8 Steps Involved in Homologous Recombination Repair Pathway
Figure 3.9 Steps Involved in Non-Homologous Repair Pathway
Figure 3.10 Genetic Disorders Caused due to Defects in DNA Repair Pathways
Figure 4.1 Basic Concept of Synthetic Lethality
Figure 4.2 Historical Evolution of Synthetic Lethality
Figure 4.3 Other Types of Synthetic Lethality Pathways
Figure 4.4 Approaches to Identify Synlet Gene Interactions
Figure 4.5 Recent News on Google: Emerging Focus Areas
Figure 4.6 Google Trend Analysis: Historical Timeline
Figure 4.7 Google Trends Analysis: Geographical Activity
Figure 4.8 Google Trends Analysis: Other Key Terms Related to Synthetic Lethality
Figure 5.1 Synthetic Lethality-based Drugs: Distribution by Phase of Development
Figure 5.2 Synthetic Lethality-based Drugs: Distribution by Type of Molecule
Figure 5.3 Synthetic Lethality-based Drugs: Distribution by Type of Therapy
Figure 5.4 Synthetic Lethality-based Drugs: Distribution by Synlet Target
Figure 5.5 Synthetic Lethality-based Drugs: Distribution by Therapeutic Area
Figure 5.6 Synthetic Lethality-based Drugs: Distribution by Target Indication
Figure 5.7 Synthetic Lethality-based Drugs: Distribution by Target Indication and Phase of Development
Figure 5.8 Synthetic Lethality-based Drugs: Distribution by Patient Segment
Figure 5.9 Synthetic Lethality-based Drugs: Distribution by Route of Administration
Figure 5.10 Synthetic Lethality-based Drug Developers: Distribution by Year of Establishment
Figure 5.11 Synthetic Lethality-based Drug Developers: Distribution by Location of Headquarters
Figure 5.12 Synthetic Lethality-based Drug Developers: Distribution by Company Size
Figure 5.13 Synthetic Lethality Drug-based Developers: Distribution by Company Size and Location of Headquarters
Figure 7.1 Social Media Analysis: Cumulative Year-Wise Activity by Volume of Tweets, January 2010-May 2019
Figure 7.2 Social Media Analysis: Historical Trends on Twitter, 2010-2019
Figure 7.3 Social Media Analysis: Evolutionary Trends on Twitter, 2010-2019
Figure 7.4 Social Media Analysis: Trending Words / Phrases on Twitter
Figure 7.5 Social Media Analysis: Most Prolific Contributors on Twitter
Figure 7.6 Social Media Analysis: Most Popular Synlet Targets / Patient Mutations on Twitter
Figure 7.7 Social Media Analysis: Year-Wise Trend in Activity for Popular Synlet Targets / Patient Mutations
Figure 7.8 Social Media Analysis: Most Popular Indications on Twitter
Figure 7.9 Social Media Analysis: Year-Wise Trend in Activity for Popular Target Indications
Figure 7.10 Social Media Analysis: Distribution by Synlet Target and Target Indication
Figure 7.11 Social Media Analysis: Year-Wise Trend in Activity for Popular Synlet Targets / Patient Mutations and Target Indications
Figure 7.12 Social Media Analysis: Multivariate Tweet Benchmark Analysis
Figure 8.1 Publication Analysis: Distribution by Type of Publication
Figure 8.2 Publication Analysis: Distribution by Study Objective
Figure 8.3 Publication Analysis: Cumulative Year-wise Trend, 2017-2019
Figure 8.4 Publication Analysis: Emerging Focus Areas
Figure 8.5 Publication Analysis: Most Popular Synlet Targets / Patient Mutations
Figure 8.6 Publication Analysis: Year-Wise Trend in Activity for Popular Synlet Targets / Patient Mutations
Figure 8.7 Publication Analysis: Most Popular Target Indications
Figure 8.8 Publication Analysis: Year-Wise Trend in Activity for Popular Target Indications
Figure 8.9 Publications Analysis: Key Journals Based on Number of Publications
Figure 8.10 Publications Analysis: Distribution by Journal Impact Factor
Figure 8.11 Publications Analysis: Key Journals Based on Journal Impact Factor
Figure 8.12 Publications Analysis: Key Research Hubs
Figure 8.13 Publications Analysis: Most Popular Authors
Figure 8.14 Publication Analysis: Most Popular Grant Bodies
Figure 8.15 Publication Analysis: Location of Grant Bodies
Figure 8.16 Publication Analysis: Multivariate Publication Benchmark Analysis
Figure 9.1 Abstract Analysis: Cumulative Year-wise Trend, 2013-2019
Figure 9.2 Abstract Analysis: Emerging Focus Areas
Figure 9.3 Abstract Analysis: Most Popular Drugs
Figure 9.4 Abstract Analysis: Most Popular Synlet Targets / Patient Mutations
Figure 9.5 Abstract Analysis: Most Popular Target Indications
Figure 9.6 Abstract Analysis: Regional Distribution of Principal Authors
Figure 9.7 Abstract Analysis: Type of Organization of Principal Authors
Figure 9.8 Abstract Analysis: Most Active Organizations
Figure 9.9 Abstract Analysis: Distribution by Author Designation
Figure 9.10 Abstract Analysis: Most Popular Authors
Figure 10.1 Grant Analysis: Cumulative Trend by Year of Award, 2014-2019
Figure 10.2 Grant Analysis: Cumulative Trend by Amount Awarded (USD Million), 2014-2019
Figure 10.3 Grant Analysis: Distribution by Administering Institute Center
Figure 10.4 Grant Analysis: Distribution by Funding Institute Center
Figure 10.5 Grant Analysis: Distribution by Support Period
Figure 10.6 Grant Analysis: Distribution by Funding Institute Center and Support Period
Figure 10.7 Grant Analysis: Most Popular NIH Funding Categorization
Figure 10.8 Grant Analysis: Analysis by Funding Mechanism
Figure 10.9 Grant Analysis: Analysis by Emerging Focus Areas
Figure 10.10 Grant Analysis: Most Popular Synlet Targets / Patient Mutations
Figure 10.11 Grant Analysis: Year-Wise Trend in Activity for Popular Synlet Targets / Patient Mutations
Figure 10.12 Grant Analysis: Most Popular Target Indications
Figure 10.13 Grant Analysis: Year-Wise Trend in Activity for Popular Target Indications
Figure 10.14 Grant Analysis: Distribution by Type of Grant Application
Figure 10.15 Grant Analysis: Most Popular NIH Departments
Figure 10.16 Grant Analysis: Distribution by Study Section
Figure 10.17 Grant Analysis: Type of Recipient Organization
Figure 10.18 Grant Analysis: Most Popular Recipient Organization
Figure 10.19 Grant Analysis: Most Popular Recipient Organizations and NIH Funding Categorization
Figure 10.20 Grant Analysis: Distribution by Grant Activity
Figure 10.21 Grant Analysis: Most Prominent Program Officers
Figure 10.22 Grant Analysis: Regional Distribution of Recipient Organization
Figure 10.23 Grant Analysis: Categorizations based on Weighted Attractiveness Scores
Figure 10.24 Grant Analysis: Multivariate Grant Attractiveness Analysis
Figure 11.1 Funding and Investment Analysis: Distribution by Type of Funding and Year of Establishment
Figure 11.2 Funding and Investment Analysis: Cumulative Number of Instances by Year, 2010-2019
Figure 11.3 Funding and Investment Analysis: Distribution by Type of Funding and Year of Investment, 2010-2019
Figure 11.4 Funding and Investment Analysis: Cumulative Amount Invested (USD Million), 2010-2019
Figure 11.5 Funding and Investment Analysis: Year-Wise Distribution of Instances by Amount (USD Million) and Type of Funding, 2010-2019
Figure 11.6 Funding and Investment Analysis: Distribution of Instances by Type of Funding, 2010-2019
Figure 11.7 Funding and Investment Analysis: Distribution of the Total Amount Invested (USD Million) by Type of Funding, 2010-2019
Figure 11.8 Funding and Investment Analysis: Summary of Amount Invested (USD Million), 2010-2019
Figure 11.9 Funding and Investment Analysis: Distribution of Number of Instances and Total Amount Invested (USD Million) by Type of Company, 2010-2019
Figure 11.10 Funding and Investment Analysis: Distribution of the Total Amount Invested (USD Million) by Purpose of Funding, 2010-2019
Figure 11.11 Funding and Investment Analysis: Distribution of the Total Amount Invested (USD Million) by Type of Molecule, 2010-2019
Figure 11.12 Funding and Investment Analysis: Distribution of the Total Amount Invested (USD Million) by Type of Molecule and Funding Type, 2010-2019
Figure 11.13 Funding and Investment Analysis: Distribution by Synlet Target
Figure 11.14 Funding and Investment Analysis: Distribution of the Total Amount Invested (USD Million) by Synlet Target, 2010-2019
Figure 11.15 Funding and Investment Analysis: Distribution by Therapeutic Area
Figure 11.16 Funding and Investment Analysis: Distribution of the Total Amount Invested (USD Million) by Therapeutic Area, 2010-2019
Figure 11.17 Funding and Investment Analysis: Distribution by Target Indication
Figure 11.18 Funding and Investment Analysis: Distribution of the Total Amount Invested (USD Million) by Target Indication
Figure 11.19 Funding and Investment Analysis: Distribution by Geography
Figure 11.20 Funding and Investment Analysis: Regional Distribution of Funding Instances
Figure 11.21 Funding and Investment Analysis: Most Active Players by Number of Instances and Amount Invested (USD Million), 2010-2019
Figure 11.22 Funding and Investment Analysis: Most Active Investors by in Terms of Number of Instances
Figure 11.23 Funding and Investment Summary, 2010-2019 (USD Million)
Figure 12.1 Target Benchmark Analysis: Clinically Validated Synlet Targets
Figure 12.2 Target Benchmark Analysis: Preclinically Validated Synlet Targets
Figure 12.3 Target Benchmark Analysis: Early Stage Research Validated Synlet Targets
Figure 13.1 Companion Diagnostics: Role in Clinical Trials
Figure 13.2 Advantages of Companion Diagnostics
Figure 13.3 Companion Diagnostics: Distribution by Synlet Target
Figure 13.4 Companion Diagnostics: Distribution by Type of Biomarker
Figure 13.5 Companion Diagnostics: Distribution by Type of Biomarker and Technology
Figure 13.6 Companion Diagnostics: Distribution by Target Indication
Figure 13.7 Companion Diagnostics: Distribution by Developer and Synlet Target
Figure 13.8 Companion Diagnostics: Most Prominent Developers
Figure 13.9 Working Process of myChoice® HRD CDx
Figure 13.10 Approval Timeline of BRACAnalysis CDx® for Olaparib
Figure 13.11 Working Process of BRACAnalysis CDx® Dignostics Kit
Figure 13.12 Companion Diagnostics Tests for Rucaparib
Figure 13.13 Companion Diagnostics in Drug Development: Market Drivers and Restraints
Figure 14.1 Overall Synthetic Lethality-based Drugs Market, 2019-2030 (USD Million)
Figure 14.2 Synthetic Lethality-based Drugs Market: Distribution by Type of Molecule, 2019 and 2030
Figure 14.3 Synthetic Lethality-based Drugs Market for Small Molecules, 2019-2030 (USD Million)
Figure 14.4 Synthetic Lethality-based Drugs Market for Biologics, 2019-2030 (USD Million)
Figure 14.5 Synthetic Lethality-based Drugs Market: Distribution by Synlet Target, 2019 and 2030
Figure 14.6 Synthetic Lethality-based Drugs Market for APE1 / REF-1, 2019-2030 (USD Million)
Figure 14.7 Synthetic Lethality-based Drugs Market for CHK1, 2019-2030 (USD Million)
Figure 14.8 Synthetic Lethality-based Drugs Market for GLS1, 2019-2030 (USD Million)
Figure 14.9 Synthetic Lethality-based Drugs Market for PARP, 2019-2030 (USD Million)
Figure 14.10 Synthetic Lethality-based Drugs Market for Polθ, 2019-2030 (USD Million)
Figure 14.11 Synthetic Lethality-based Drugs Market for WEE1, 2019-2030 (USD Million)
Figure 14.12 Synthetic Lethality-based Drugs Market: Distribution by Target Indication, 2019 and 2030
Figure 14.13 Synthetic Lethality-based Drugs Market for Breast Cancer, 2019-2030 (USD Million)
Figure 14.14 Synthetic Lethality-based Drugs Market for Cervical / Anogenital Cancer, 2019-2030 (USD Million)
Figure 14.15 Synthetic Lethality-based Drugs Market for Diabetic Macular Edema, 2019-2030 (USD Million)
Figure 14.16 Synthetic Lethality-based Drugs Market for Gastric Cancer, 2019-2030 (USD Million)
Figure 14.17 Synthetic Lethality-based Drugs Market for Lung Cancer, 2019-2030 (USD Million)
Figure 14.18 Synthetic Lethality-based Drugs Market for Ovarian Cancer, 2019-2030 (USD Million)
Figure 14.19 Synthetic Lethality-based Drugs Market for Renal Cell Cancer, 2019-2030 (USD Million)
Figure 14.20 Synthetic Lethality-based Drugs Market: Distribution by Route of Administration, 2019 and 2030
Figure 14.21 Synthetic Lethality-based Drugs Market for Oral Therapies, 2019-2030 (USD Million)
Figure 14.22 Synthetic Lethality-based Drugs Market for Intravenous Therapies, 2019-2030 (USD Million)
Figure 14.23 Synthetic Lethality-based Drugs Market: Distribution by Geography, 2019 and 2030
Figure 14.24 Synthetic Lethality-based Drugs Market in the US, 2019-2030 (USD Million)
Figure 14.25 Synthetic Lethality-based Drugs Market in France, 2019-2030 (USD Million)
Figure 14.26 Synthetic Lethality-based Drugs Market in Germany, 2019-2030 (USD Million)
Figure 14.27 Synthetic Lethality-based Drugs Market in Italy, 2019-2030 (USD Million)
Figure 14.28 Synthetic Lethality-based Drugs Market in Spain, 2019-2030 (USD Million)
Figure 14.29 Synthetic Lethality-based Drugs Market in the UK, 2019-2030 (USD Million)
Figure 14.30 Synthetic Lethality-based Drugs Market in Australia, 2019-2030 (USD Million)
Figure 14.31 Synthetic Lethality-based Drugs Market in China, 2019-2030 (USD Million)
Figure 14.32 Synthetic Lethality-based Drugs Market in Japan, 2019-2030 (USD Million)
Figure 14.33 Niraparib (GlaxoSmithKline): Sales Forecast, till 2030 (USD Million)
Figure 14.34 Olaparib (AstraZeneca): Sales Forecast, till 2030 (USD Million)
Figure 14.35 Rucaparib (Clovis Oncology): Sales Forecast, till 2030 (USD Million)
Figure 14.36 Talazoparib (Pfizer): Sales Forecast, till 2030 (USD Million)
Figure 14.37 Pamiparib (BeiGene): Sales Forecast, till 2030 (USD Million)
Figure 14.38 Veliparib (AbbVie): Sales Forecast, till 2030 (USD Million)
Figure 14.39 Adavosertib (AstraZeneca): Sales Forecast, till 2030 (USD Million)
Figure 14.40 APX3330 (Apexian Pharmaceuticals): Sales Forecast, till 2030 (USD Million)
Figure 14.41 CX-5461 (Senhwa Biosciences): Sales Forecast, till 2030 (USD Million)
Figure 14.42 SRA737-01 (Sierra Oncology): Sales Forecast, till 2030 (USD Million)
Figure 14.43 SRA737-02 (Sierra Oncology): Sales Forecast, till 2030 (USD Million)
Figure 14.44 Telaglenastat (Calithera Biosciences): Sales Forecast, till 2030 (USD Million)
Figure 14.45 Overall Synthetic Lethality-based Drugs Market, 2019, 2025 and 2030, Base, Optimistic and Conservative Scenario (USD Million)
Table 3.1 Key Components of DNA Repair Systems
Table 3.2 Difference between HRR and Non-Homologous End Joining Pathway
Table 3.3 DNA Damage Repair Related Inheritable Mutations
Table 5.1 Synthetic Lethality-based Drugs: Marketed and Development Pipeline
Table 5.2 Synthetic Lethality-based Drugs: Information on Target Indications
Table 5.3 Synthetic Lethality-based Drugs: Information on Type of Therapy and Route of Administration
Table 5.4 Synthetic Lethality-based Drugs: List of Screening Platforms
Table 5.5 Synthetic Lethality-based Drugs: List of Drug Developers / Screening Platform Providers
Table 6.1 AbbVie: Key Highlights
Table 6.2 Drug Profile: Veliparib (ABT-888)
Table 6.3 AbbVie: Recent Developments and Future Outlook
Table 6.4 AstraZeneca: Key Highlights
Table 6.5 Drug Profile: Olaparib (Lynparza®)
Table 6.6 Drug Profile: AZD6738
Table 6.7 Drug Profile: AZD1775
Table 6.8 AstraZeneca: Recent Developments and Future Outlook
Table 6.9 BeiGene: Key Highlights
Table 6.10 Drug Profile: Pamiparib (BGB-290)
Table 6.11 BeiGene: Recent Developments and Future Outlook
Table 6.12 Clovis Oncology: Key Highlights
Table 6.13 Drug Profile: Rucaparib (Rubraca®)
Table 6.14 Clovis Oncology: Recent Developments and Future Outlook
Table 6.15 GlaxoSmithKline: Key Highlights
Table 6.16 Drug Profile: Niraparib (Zejula®)
Table 6.17 GlaxoSmithKline: Recent Developments and Future Outlook
Table 6.18 Pfizer: Key Highlights
Table 6.19 Drug Profile: Talazoparib (BMN 673)
Table 6.20 Pfizer: Recent Developments and Future Outlook
Table 6.21 AtlasMedx: Key Highlights
Table 6.22 Chordia Therapeutics: Key Highlights
Table 6.23 IDEAYA Biosciences: Key Highlights
Table 6.24 Mission Therapeutics: Key Highlights
Table 6.25 Repare Therapeutics: Key Highlights
Table 6.26 Sierra Oncology: Key Highlights
Table 6.27 SyntheX Labs: Key Highlights
Table 7.1 Social Media Analysis: Most Popular Tweets
Table 8.1 Publication Analysis: List of Recent Publications, 2019
Table 8.2 Synthetic Lethality: Details on Popular Authors
Table 8.3 Publication Analysis: List of Most Valued Publications
Table 9.1 Abstract Analysis: List of ASCO Abstracts, 2013-2019
Table 9.2 Abstract Analysis: Details on Principal Authors
Table 10.1 Grant Analysis: List of Most Attractive Grants
Table 11.1 Synthetic Lethality: Funding and Investments, Information on Funding Year, Type, Amount and Investor 2010-2019
Table 11.2 Synthetic Lethality: Funding and Investments, Information on Company Type and Focus Area 2010-2019
Table 11.3 Synthetic Lethality: Funding and Investments, Information on Drug Class, Synlet Target, Target Indication and Therapeutic Area 2010-2019
Table 11.4 Funding and Investment Analysis: Summary of Investments
Table 12.1 List of Big Pharmaceutical Players and Key Targets Under Investigation
Table 13.1 Companion Diagnostics: List of Available / Under Development Tests
Table 13.2 Companion Diagnostics: Information on Drug, Indication, Device Type and Sample Used
Table 13.3 Companion Diagnostics: Potential Partnership Opportunities
Table 14.1 Synthetic Lethality-based Drugs: Promising Drug Candidates
Table 14.2 Synthetic Lethality-based Drugs Forecast Assumptions: Price Estimations in Key Geographies
Table 14.3 Niraparib (GlaxoSmithKline): Target Patient Population
Table 14.4 Niraparib (GlaxoSmithKline): Net Present Value (USD Million)
Table 14.5 Niraparib (GlaxoSmithKline): Value Creation Analysis (USD Million)
Table 14.6 Olaparib (AstraZeneca): Target Patient Population
Table 14.7 Olaparib (AstraZeneca): Net Present Value (USD Million)
Table 14.8 Olaparib (AstraZeneca): Value Creation Analysis (USD Million)
Table 14.9 Rucaparib (Clovis Oncology): Target Patient Population
Table 14.10 Rucaparib (Clovis Oncology): Net Present Value (USD Million)
Table 14.11 Rucaparib (Clovis Oncology): Value Creation Analysis (USD Million)
Table 14.12 Talazoparib (Pfizer): Target Patient Population
Table 14.13 Talazoparib (Pfizer): Net Present Value (USD Million)
Table 14.14 Talazoparib (Pfizer): Value Creation Analysis (USD Million)
Table 14.15 Pamiparib (BeiGene): Target Patient Population
Table 14.16 Pamiparib (BeiGene): Net Present Value (USD Million)
Table 14.17 Pamiparib (BeiGene): Value Creation Analysis (USD Million)
Table 14.18 Veliparib (AbbVie): Target Patient Population
Table 14.19 Veliparib (AbbVie): Net Present Value (USD Million)
Table 14.20 Veliparib (AbbVie): Value Creation Analysis (USD Million)
Table 14.21 Adavosertib (AstraZeneca): Target Patient Population
Table 14.22 Adavosertib (AstraZeneca): Net Present Value (USD Million)
Table 14.23 Adavosertib (AstraZeneca): Value Creation Analysis (USD Million)
Table 14.24 APX3330 (Apexian Pharmaceuticals): Target Patient Population
Table 14.25 APX3330 (Apexian Pharmaceuticals): Net Present Value (USD Million)
Table 14.26 APX3330 (Apexian Pharmaceuticals): Value Creation Analysis (USD Million)
Table 14.27 CX-5461 (Senhwa Biosciences): Target Patient Population
Table 14.28 CX-5461 (Senhwa Biosciences): Net Present Value (USD Million)
Table 14.29 CX-5461 (Senhwa Biosciences): Value Creation Analysis (USD Million)
Table 14.30 SRA 737-01 (Sierra Oncology): Target Patient Population
Table 14.31 SRA 737-01 (Sierra Oncology): Net Present Value (USD Million)
Table 14.32 SRA 737-01 (Sierra Oncology): Value Creation Analysis (USD Million)
Table 14.33 SRA 737-02 (Sierra Oncology): Target Patient Population
Table 14.34 SRA 737-02 (Sierra Oncology): Net Present Value (USD Million)
Table 14.35 SRA 737-02 (Sierra Oncology): Value Creation Analysis (USD Million)
Table 14.36 Telaglenastat (Calithera Biosciences): Target Patient Population
Table 14.37 Telaglenastat (Calithera Biosciences): Net Present Value (USD Million)
Table 14.38 Telaglenastat (Calithera Biosciences): Value Creation Analysis (USD Million)
Table 16.1 Artios Pharma: Company / Organization Snapshot
Table 16.2 IMPACT Therapeutics: Company / Organization Snapshot
Table 16.3 Harvard Medical School: Company / Organization Snapshot
Table 16.4 Panjab University: Company / Organization Snapshot
Table 16.5 UbiQ: Company / Organization Snapshot
Table 17.1 Google Trend Analysis: Historical Timeline
Table 17.2 Google Trends Analysis: Geographical Activity
Table 17.3 Google Trends Analysis: Other Key Terms Related to Synthetic Lethality
Table 17.4 Synthetic Lethality-based Drugs: Distribution by Phase of Development
Table 17.5 Synthetic Lethality-based Drugs: Distribution by Type of Molecule
Table 17.6 Synthetic Lethality-based Drugs: Distribution by Type of Therapy
Table 17.7 Synthetic Lethality-based Drugs: Distribution by Type of Synlet Target
Table 17.8 Synthetic Lethality-based Drugs: Distribution by Therapeutic Area
Table 17.9 Synthetic Lethality-based Drugs: Distribution by Target Indication
Table 17.10 Synthetic Lethality-based Drugs: Distribution by Target Indication and Phase of Development
Table 17.11 Synthetic Lethality-based Drugs: Distribution by Type of Patient Segment
Table 17.12 Synthetic Lethality-based Drugs: Distribution by Route of Administration
Table 17.13 Synthetic Lethality-based Drug Developers: Distribution by Year of Establishment
Table 17.14 Synthetic Lethality-based Drug Developers: Distribution by Location of Headquarters
Table 17.15 Synthetic Lethality-based Drug Developers: Distribution by Company Size
Table 17.16 Synthetic Lethality-based Drug Developers: Distribution by Company Size and Location of Headquarters
Table 17.17 Synthetic Lethality-based Drug Developers: Leading Players
Table 17.18 Social Media Analysis: Cumulative Year-Wise Activity by Volume of Tweets, January 2010- May 2019
Table 17.19 Social Media Analysis: Historical Trends on Twitter, 2010-2019
Table 17.20 Social Media Analysis: Most Prolific Contributors on Twitter
Table 17.22 Social Media Analysis: Most Popular Synlet Targets / Patient Mutations on Twitter
Table 17.22 Social Media Analysis: Year-Wise Trend in Activity for Popular Synlet Targets / Patient Mutations
Table 17.23 Social Media Analysis: Most Popular Indications on Twitter
Table 17.24 Social Media Analysis: Year-Wise Trend in Activity for Popular Synthetic Target Indications
Table 17.25 Social Media Analysis: Distribution by Synlet Target and Target Indication
Table 17.26 Social Media Analysis: Year-Wise Trend in Activity for Popular Synlet Targets / Patient Mutations and Indications
Table 17.27 Publication Analysis: Distribution by Type of Publication
Table 17.28 Publication Analysis: Distribution by Study Objective
Table 17.29 Publication Analysis: Cumulative Year-wise Trend, 2017-2019
Table 17.30 Publication Analysis: Most Popular Synlet Targets
Table 17.31 Publication Analysis: Year-Wise Trend for Most Popular Synlet Targets / Patient Mutations
Table 17.32 Publication Analysis: Most Popular Target Indications
Table 17.33 Publication Analysis: Year-Wise Trend for Most Popular Target Indications
Table 17.34 Publication Analysis: Key Journals Based on Number of Publications
Table 17.35 Publication Analysis: Distribution by Journal Impact Factor
Table 17.36 Publication Analysis: Key Journals Based on Journal Impact Factor
Table 17.37 Publication Analysis: Key Research Hubs
Table 17.38 Publication Analysis: Most Popular Authors
Table 17.39 Publication Analysis: Most Popular Grant Bodies
Table 17.40 Publication Analysis: Location of Grant Bodies
Table 17.41 Abstract Analysis: Cumulative Year-wise Trend, 2013-2019
Table 17.42 Abstract Analysis: Most Popular Drugs
Table 17.43 Abstract Analysis: Most Popular Synlet Targets / Patient Mutations
Table 17.44 Abstract Analysis: Most Popular Target Indications
Table 17.45 Abstract Analysis: Regional Distribution of Principal Authors
Table 17.46 Abstract Analysis: Type of Organization of Principal Authors
Table 17.47 Abstract Analysis: Most Active Organizations
Table 17.48 Abstract Analysis: Distribution by Author Designation
Table 17.49 Abstract Analysis: Most Popular Authors
Table 17.50 Grant Analysis: Cumulative Trend by Year of Award, 2014-2019
Table 17.51 Grant Analysis: Cumulative Trend by Amount Awarded (USD Million), 2014- 2019
Table 17.52 Grant Analysis: Distribution by Administering Institute Center
Table 17.53 Grant Analysis: Distribution by Funding Institute Center
Table 17.54 Grant Analysis: Distribution by Support Period
Table 17.55 Grant Analysis: Distribution by Funding Institute Center and Support Period
Table 17.56 Grant Analysis: Most Popular NIH Funding Categorization
Table 17.57 Grant Analysis: Analysis by Funding Mechanism
Table 17.58 Grant Analysis: Most Popular Synlet Targets / Patient Mutations
Table 17.59 Grant Analysis: Year-Wise Trend in Activity for Popular Synlet Targets / Patient Mutations
Table 17.60 Grant Analysis: Popular Target Indications
Table 17.61 Grant Analysis: Year-Wise Trend in Activity for Popular Target Indications
Table 17.62 Grant Analysis: Distribution by Type of Grant Application
Table 17.63 Grant Analysis: Most Popular NIH Departments
Table 17.64 Grant Analysis: Distribution by Study Section
Table 17.65 Grant Analysis: Type of Recipient Organization
Table 17.66 Grant Analysis: Most Popular Recipient Organization
Table 17.67 Grant Analysis: Most Popular Recipient Organizations and NIH Spending Categorization
Table 17.68 Grant Analysis: Distribution by Grant Activity
Table 17.69 Grant Analysis: Most Prominent Program Officers
Table 17.70 Grant Analysis: Regional Distribution of Recipient Organization
Table 17.71 Funding and Investment Analysis: Distribution by Type of Funding and Year of Establishment
Table 17.72 Funding and Investment Analysis: Cumulative Number of Instances by Year, 2010-2019
Table 17.73 Funding and Investment Analysis: Distribution by Type of Funding and Year of Investment, 2010-2019
Table 17.74 Funding and Investment Analysis: Cumulative Amount Invested (USD Million), 2010-2019
Table 17.75 Funding and Investment Analysis: Year-Wise Distribution of Instances by Amount (USD Million) and Type of Funding, 2010-2019
Table 17.76 Funding and Investment Analysis: Distribution of Instances by Type of Funding, 2010-2019
Table 17.77 Funding and Investment Analysis: Distribution of the Total Amount Invested (USD Million) by Type of Funding, 2010-2019
Table 17.78 Funding and Investment Analysis: Summary of Amount Invested (USD Million), 2010-2019
Table 17.79 Funding and Investment Analysis: Distribution of Number of Instances and Total Amount Invested (USD Million) by Type of Company, 2010-2019
Table 17.80 Funding and Investment Analysis: Distribution of the Total Amount Invested (USD Million) by Purpose of Funding, 2010-2019
Table 17.81 Funding and Investment Analysis: Distribution of the Total Amount Invested (USD Million) by Type of Molecule, 2010-2019
Table 17.82 Funding and Investment Analysis: Distribution of the Total Amount Invested (USD Million) by Type of Molecule and Funding Type, 2010-2019
Table 17.83 Funding and Investment Analysis: Distribution by Synlet Target
Table 17.84 Funding and Investment Analysis: Distribution of the Total Amount Invested (USD Million) by Synlet Target, 2010-2019
Table 17.85 Funding and Investment Analysis: Distribution by Therapeutic Area
Table 17.86 Funding and Investment Analysis: Distribution of the Total Amount Invested (USD Million) by Therapeutic Area, 2010-2019
Table 17.87 Funding and Investment Analysis: Distribution by Target Indication
Table 17.88 Funding and Investment Analysis: Distribution of the Total Amount Invested (USD Million) by Target Indication
Table 17.89 Funding and Investment Analysis: Distribution by Geography
Table 17.90 Funding and Investment Analysis: Regional Distribution of Funding Instances
Table 17.91 Funding and Investment Analysis: Most Active Players by Number of Instances and Amount Invested (USD Million), 2010-2019
Table 17.92 Funding and Investment Analysis: Most Active Investors by in Terms of Number of Instances
Table 17.93 Companion Diagnostics: Distribution by Synlet Target
Table 17.94 Companion Diagnostics: Distribution by Type of Biomarker
Table 17.95 Companion Diagnostics: Distribution by Type of Biomarker and Technology
Table 17.96 Companion Diagnostics: Distribution by Target Indication
Table 17.97 Companion Diagnostics: Distribution by Developer and Synlet Target
Table 17.98 Companion Diagnostics: Most Prominent Developers
Table 17.99 Overall Synthetic Lethality-based Drugs Market, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.100 Synthetic Lethality-based Drugs Market: Distribution by Type of Molecule, 2019 and 2030
Table 17.101 Synthetic Lethality-based Drugs Market for Small Molecules, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.102 Synthetic Lethality-based Drugs Market for Biologics, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.103 Synthetic Lethality-based Drugs Market: Distribution by Synlet Target, 2019 and 2030
Table 17.104 Synthetic Lethality-based Drugs Market for APE1 / REF-1, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.105 Synthetic Lethality-based Drugs Market for CHK1, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.106 Synthetic Lethality-based Drugs Market for GLS1, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.107 Synthetic Lethality-based Drugs Market for PARP, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.108 Synthetic Lethality-based Drugs Market for Polθ, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.109 Synthetic Lethality-based Drugs Market for WEE1, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.110 Synthetic Lethality-based Drugs Market: Distribution by Target Indication, 2019 and 2030
Table 17.111 Synthetic Lethality-based Drugs Market for Breast Cancer, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.112 Synthetic Lethality-based Drugs Market for Cervical / Anogenital Cancer, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.113 Synthetic Lethality-based Drugs Market for Diabetic Macular Edema, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.114 Synthetic Lethality-based Drugs Market for Gastric Cancer, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.115 Synthetic Lethality-based Drugs Market for Lung Cancer, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.116 Synthetic Lethality-based Drugs Market for Ovarian Cancer, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.117 Synthetic Lethality-based Drugs Market for Renal Cell Cancer, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.118 Synthetic Lethality-based Drugs Market: Distribution by Route of Administration, 2019 and 2030
Table 17.119 Synthetic Lethality-based Drugs Market for Oral Therapies, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.120 Synthetic Lethality-based Drugs Market for Intravenous Therapies, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.121 Synthetic Lethality-based Drugs Market: Distribution by Geography, 2019 and 2030
Table 17.122 Synthetic Lethality-based Drugs Market in the US, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.123 Synthetic Lethality-based Drugs Market in France, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.124 Synthetic Lethality-based Drugs Market in Germany, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.125 Synthetic Lethality-based Drugs Market in Italy, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.126 Synthetic Lethality-based Drugs Market in Spain, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.127 Synthetic Lethality-based Drugs Market in the UK, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.128 Synthetic Lethality-based Drugs Market in Australia, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.129 Synthetic Lethality-based Drugs Market in China, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.130 Synthetic Lethality-based Drugs Market in Japan, 2019-2030: Base, Optimistic, Conservative Case (USD Million)
Table 17.131 Niraparib (GlaxoSmithKline): Sales Forecast, till 2030 Base, Optimistic, Conservative Case (USD Million)
Table 17.132 Olaparib (AstraZeneca): Sales Forecast, till 2030 Base, Optimistic, Conservative Case (USD Million)
Table 17.133 Rucaparib (Clovis Oncology): Sales Forecast, till 2030 Base, Optimistic, Conservative Case (USD Million)
Table 17.134 Talazoparib (Pfizer): Sales Forecast, till 2030 Base, Optimistic, Conservative Case (USD Million)
Table 17.135 Pamiparib (BeiGene): Sales Forecast, till 2030 Base, Optimistic, Conservative Case (USD Million)
Table 17.136 Veliparib (AbbVie): Sales Forecast, till 2030 Base, Optimistic, Conservative Case (USD Million)
Table 17.137 Adavosertib (AstraZeneca): Sales Forecast, till 2030 Base, Optimistic, Conservative Case (USD Million)
Table 17.138 APX3330 (Apexian Pharmaceuticals): Sales Forecast, till 2030 Base, Optimistic, Conservative Case (USD Million)
Table 17.139 CX-5461 (Senhwa Biosciences): Sales Forecast, till 2030 Base, Optimistic, Conservative Case (USD Million)
Table 17.140 SRA737-01 (Sierra Oncology): Sales Forecast, till 2030 Base, Optimistic, Conservative Case (USD Million)
Table 17.141 SRA737-02 (Sierra Oncology): Sales Forecast, till 2030 Base, Optimistic, Conservative Case (USD Million)
Table 17.142 Telaglenastat (Calithera Biosciences): Sales Forecast, till 2030 Base, Optimistic, Conservative Case (USD Million)
Table 17.143 Overall Synthetic Lethality-based Drugs Market, 2019, 2025 and 2030, Base, Optimistic and Conservative Scenario
The following companies and organizations have been mentioned in the report.
The USD 6.5 billion (by 2030) financial opportunity within the synthetic lethality market has been analyzed across the following segments:
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