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New studies link cell cycle proteins to immunosurveillance of premalignant cells

Posted in Apoptosis, Biological Networks, Biological Networks, Gene Regulation and Evolution, Cancer - General, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer-Immune Interactions, Cell Biology, Signaling & Cell Circuits, Circulating Tumor Cells (CTC), Disease Biology, DNA repair, Efficacy of Anti-Tumor T Cells, Exosomes, Exosomes: Natural Carriers for siRNA Delivery, Immune Modulatory, Immuno-Oncology & Genomics, Immunology, KRAS Mutation, Modulating Macrophages in Cancer Immunotherapy, NK Cell-Based Cancer Immunotherapy, TP53 - Germline mutations, tagged CDKI, cell cycle, cell cycle arrest, cell cycle protein, cellular senescence, DNA repair or transcription factor genes, Immunology, immunosuppression, immunosurveillance, NF-kB, p21, p53, premalignant, transcriptional, transcriptional regulation, tumor suppressors on December 16, 2021| Leave a Comment »

New studies link cell cycle proteins to immunosurveillance of premalignant cells

Curator: Stephen J. Williams, Ph.D.

The following is from a Perspectives article in the journal Science by Virinder Reen and Jesus Gil called “Clearing Stressed Cells: Cell cycle arrest produces a p21-dependent secretome that initaites immunosurveillance of premalignant cells”. This is a synopsis of the Sturmlechener et al. research article in the same issue (2).

Complex organisms repair stress-induced damage to limit the replication of faulty cells that could drive cancer. When repair is not possible, tissue homeostasis is maintained by the activation of stress response programs such as apoptosis, which eliminates the cells, or senescence, which arrests them (1). Cellular senescence causes the arrest of damaged cells through the induction of cyclin-dependent kinase inhibitors (CDKIs) such as p16 and p21 (2). Senescent cells also produce a bioactive secretome (the senescence-associated secretory phenotype, SASP) that places cells under immunosurveillance, which is key to avoiding the detrimental inflammatory effects caused by lingering senescent cells on surrounding tissues. On page 577 of this issue, Sturmlechner et al. (3) report that induction of p21 not only contributes to the arrest of senescent cells, but is also an early signal that primes stressed cells for immunosurveillance.Senescence is a complex program that is tightly regulated at the epigenetic and transcriptional levels. For example, exit from the cell cycle is controlled by the induction of p16 and p21, which inhibit phosphorylation of the retinoblastoma protein (RB), a transcriptional regulator and tumor suppressor. Hypophosphorylated RB represses transcription of E2F target genes, which are necessary for cell cycle progression. Conversely, production of the SASP is regulated by a complex program that involves super-enhancer (SE) remodeling and activation of transcriptional regulators such as nuclear factor κB (NF-κB) or CCAAT enhancer binding protein–β (C/EBPβ) (4).

Senescence is a complex program that is tightly regulated at the epigenetic and transcriptional levels. For example, exit from the cell cycle is controlled by the induction of p16 and p21, which inhibit phosphorylation of the retinoblastoma protein (RB), a transcriptional regulator and tumor suppressor. Hypophosphorylated RB represses transcription of E2F target genes, which are necessary for cell cycle progression. Conversely, production of the SASP is regulated by a complex program that involves super-enhancer (SE) remodeling and activation of transcriptional regulators such as nuclear factor κB (NF-κB) or CCAAT enhancer binding protein–β (C/EBPβ) (4).

Sturmlechner et al. found that activation of p21 following stress rapidly halted cell cycle progression and triggered an internal biological timer (of ∼4 days in hepatocytes), allowing time to repair and resolve damage (see the figure). In parallel, C-X-C motif chemokine 14 (CXCL14), a component of the PASP, attracted macrophages to surround and closely surveil these damaged cells. Stressed cells that recovered and normalized p21 expression suspended PASP production and circumvented immunosurveillance. However, if the p21-induced stress was unmanageable, the repair timer expired, and the immune cells transitioned from surveillance to clearance mode. Adjacent macrophages mounted a cytotoxic T lymphocyte response that destroyed damaged cells. Notably, the overexpression of p21 alone was sufficient to orchestrate immune killing of stressed cells, without the need of a senescence phenotype. Overexpression of other CDKIs, such as p16 and p27, did not trigger immunosurveillance, likely because they do not induce CXCL14 expression.In the context of cancer, senescent cell clearance was first observed following reactivation of the tumor suppressor p53 in liver cancer cells. Restoring p53 signaling induced senescence and triggered the elimination of senescent cells by the innate immune system, prompting tumor regression (5). Subsequent work has revealed that the SASP alerts the immune system to target preneoplastic senescent cells. Hepatocytes expressing the oncogenic mutant NRAS^G12V (Gly¹²→Val) become senescent and secrete chemokines and cytokines that trigger CD4⁺ T cell–mediated clearance (6). Despite the relevance for tumor suppression, relatively little is known about how immunosurveillance of oncogene-induced senescent cells is initiated and controlled.

Source of image: Reen, V. and Gil, J. Clearing Stressed Cells. Science Perspectives 2021;Vol 374(6567) p 534-535.

References

2. Sturmlechner I, Zhang C, Sine CC, van Deursen EJ, Jeganathan KB, Hamada N, Grasic J, Friedman D, Stutchman JT, Can I, Hamada M, Lim DY, Lee JH, Ordog T, Laberge RM, Shapiro V, Baker DJ, Li H, van Deursen JM. p21 produces a bioactive secretome that places stressed cells under immunosurveillance. Science. 2021 Oct 29;374(6567):eabb3420. doi: 10.1126/science.abb3420. Epub 2021 Oct 29. PMID: 34709885.

CAR T-Cell Therapy Market: 2020 – 2027 – Global Market Analysis and Industry Forecast

Posted in Cancer and Current Therapeutics, Cancer Vaccines: Targeting Cancer Genes for Immunotherapy, CAR-T, combination immunotherapies., Immune Engineering, Immune Modulatory, Immunotherapy, Modulating Macrophages in Cancer Immunotherapy, Pharmaceutical Industry Competitive Intelligence, Pharmacogenomics, Synergistic Innate and Adaptive Immunotherapy on October 12, 2020| Leave a Comment »

CAR T-CELL THERAPY MARKET: 2020 – 2027

G L O B A L M A R K E T A N A L Y S I S A N D

I N D U S T R Y F O R E C A S T

DISCLAIMER

LPBI Group’s decision to publish the Table of Contents of this Report does not imply endorsement of the Report

Aviva Lev-Ari, PhD, RN, Founder 1.0 & 2.0 LPBI Group

Guest Reporter: MIKE WOOD

Marketing Executive
BIOTECH FORECASTS

ABOUT BIOTECH FORECASTS

BIOTECH FORECASTS is a full-service market research and business- consulting firm primarily focusing on healthcare, pharmaceutical, and biotechnology industries. BIOTECH FORECASTS provides global as well as medium and small Pharmaceutical and Biotechnology businesses with unmatched quality of “Market Research Reports” and “Business Intelligence Solutions”. BIOTECH FORECASTS has a targeted view to provide business insights and consulting to assist its clients to make strategic business decisions, and achieve sustainable growth in their respective market domain.

UPDATED on 10/13/2020

CAR T-CELL THERAPY MARKET

Published on October 13, 2020

Mike Wood

Marketing Executive at Biotech Forecasts

1 article

CAR T-cell therapy as a part of adoptive cell therapy (ACT), has become one of the most rapidly growing and promising fields in the Immuno-oncology. As compared to the conventional cancer therapies, CAR T-cell therapy is the single-dose solution for the treatment of various cancers, significantly for some lethal forms of hematological malignancies.

CAR T-cell therapy mainly involves the use of engineered T-cells, the process starts with the extraction of T-cells through leukapheresis, either from the patient (autologous) or a healthy donor (allogeneic). After the expression of a synthetic receptor (Chimeric Antigen Receptor) in the lab, the altered T-cells are expanded to the right dose and administered into the patient’s body. where they target and attach to a specific antigen on the tumor surface, to kill the cancerous cells by igniting the apoptosis.

The global CAR T-cell therapy market was valued at $734 million in 2019 and is estimated to reach $4,078 million by 2027, registering a CAGR of 23.91% from 2020 to 2027.

Factors that drive the market growth involve, (1) Increased in funding for R&D activities pertaining to cell and gene therapy. By H1 2020 cell and gene therapy companies set new records in the fundraising despite the pandemic crisis. For Instance, by June 2020 totaled $1,452 Million raised in Five IPOs including, Legend Biotech ($487M), Passage Bio ($284M), Akouos ($244M), Generation Bio ($230M), and Beam Therapeutics ($207M), which is 2.5 times the total IPO of 2019.

Moreover, in 2019 cell therapy companies specifically have raised $560 million of venture capital, including Century Therapeutics ($250M), Achilles Therapeutics Ltd. ($121M in series B), NKarta Therapeutics Inc. ($114M), and Tmunity Therapeutics ($75M in Series B).

(2) Increased in No. of Approved Products, By July 2020, there are a total of 03 approved CAR T-cell therapy products, including KYMRIAH®, YESCARTA®, and the most recently approved TECARTUS™ (formerly KTE-X19). Furthermore, two CAR T-cell therapies BB2121, and JCAR017 are expected to get the market approval by the end of 2020 or in early 2021.

Other factors that boost the market growth involves; (3) increase in government support, (4) ethical acceptance of Cell and Gene therapy for cancer treatment, (5) rise in the prevalence of cancer, and (6) an increase in awareness regarding the CAR T-cell therapy.

However, high costs associated with the treatment (KYMRIAH® cost around $475,000, and YESCARTA® costs $373,000 per infusion), long production hours, obstacles in treating solid tumors, and unwanted immune responses & potential side effects might hamper the market growth.

The report also presents a detailed quantitative analysis of the current market trends and future estimations from 2020 to 2027.

The forecasts cover 2 Approach Types, 5 Antigen Types, 5 Application Types, 4 Regions, and 14 Countries.

The report comes with an associated file covering quantitative data from all numeric forecasts presented in the report, as well as with a Clinical Trials Data File.

KEY FINDINGS

The report has the following key findings:

The global CAR T-cell therapy market accounted for $734 million in 2019 and is estimated to reach $4,078 million by 2027, registering a CAGR of 23.91% from 2020 to 2027.

By approach type the autologous segment was valued at $655.26 million in 2019 and is estimated to reach $ 3,324.52 million by 2027, registering a CAGR of 22.51% from 2020 to 2027.

By approach type, the allogeneic segment exhibits the highest CAGR of 32.63%.

Based on the Antigen segment CD19 was the largest contributor among the other segments in 2019.

The Acute lymphocytic leukemia (ALL) segment generated the highest revenue and is expected to continue its dominance in the future, followed by the Diffuse large B-cell lymphoma (DLBCL) segment.

North America dominated the global CAR T-cell therapy market in 2019 and is projected to continue its dominance in the future.

China is expected to grow the highest in the Asia-Pacific region during the forecast period.

TOPICS COVERED

The report covers the following topics:

Market Drivers, Restraints, and Opportunities

Porters Five Forces Analysis

CAR T-Cell Structure, Generations, Manufacturing, and Pricing Models

Top Winning Strategies, Top Investment Pockets

Analysis of by Approach Type, Antigen Type, Application, and Region

51 Company Profiles, Product Portfolio, and Key Strategies

Approved Products Profiles, and list of Expected Approvals

COVID-19 Impact on the Cell and Gene Therapy Industry

CAR T-cell therapy clinical trials analysis from 1997 to 2019

Market analysis and forecasts from 2020 to 2027

FORECAST SEGMENTATION

By Approach Type

Autologous

Allogeneic

By Antigen Type

CD19

CD20

BCMA

MSLN

Others

By Application

Acute lymphoblastic leukemia (ALL)

Diffuse large B-Cell lymphoma (DLBCL)

Multiple Myeloma (MM)

Acute Myeloid Leukemia (AML)

Other Cancer Indications

By Region

North America: USA, Canada, Mexico

Europe: UK, Germany, France, Spain, Italy, Rest of Europe

Asia-Pacific: China, Japan, India, South Korea, Rest of Asia-Pacific

LAMEA: Brazil, South Africa, Rest of LAMEA

Contact at info@biotechforecasts.com for any Queries or Free Report Sample

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Published by

Mike Wood

Marketing Executive at Biotech Forecasts

Published • 10h

1 article

The global CAR T-cell therapy market was valued at $734 million in 2019 and is estimated to reach $4,078 million by 2027, registering a CAGR of 23.91% from 2020 to 2027. hashtagcelltherapy hashtaggenetherapy hashtagimmunotherapy hashtagcancertreatment hashtagcartcell hashtagregenerativemedicine hashtagbiotech hashtagcancer

CHAPTER 1: INTRODUCTION

1.1 REPORT DESCRIPTION 17

1.2 TOPICS COVERED 19

1.3 KEY MARKET SEGMENTS 20

1.4 KEY BENEFITS 21

1.5 RESEARCH METHODOLOGY 21

1.6 TARGET AUDIENCE 22

1.7 COMPANIES MENTIONED 23

CHAPTER 2: EXECUTIVE SUMMARY

2.1 EXECUTIVE SUMMARY 26

2.2 CXO PROSPECTIVE 29

CHAPTER 3: MARKET OVERVIEW

3.1 MARKET DEFINITION AND SCOPE 30

3.2 KEY FINDINGS 31

3.3 TOP INVESTMENT POCKETS 32

3.4 TOP WINNING STRATEGIES 33

3.4.1.Top winning strategies, by year, 2017-2019* 34

3.4.2.Top winning strategies, by development, 2017-2019*(%) 34

3.4.3.Top winning strategies, by company, 2017-2019* 35

3.5 TOP PLAYER POSITIONING, BY PIPELINE VOLUME, 2019 38

3.6 PORTERS FIVE FORCES ANALYSIS 39

3.7 COVID19 IMPACT ON CELL AND GENE THERAPY (CGT) INDUSTRY 41

3.8 MARKET DYNAMICS 46

3.8.1    Drivers 46

3.8.1.1 Increase in funding for R&D activities of CAR T-cell therapy 46

3.8.1.2 The rise in the prevalence of cancer 47

3.8.1.3 Increase in awareness regarding CAR T-cell therapy 47

3.8.2    Restrains 48

3.8.2.1 The high cost of CAR T-cell therapy treatment 48

3.8.2.2 Unwanted immune responses and side effects 48

3.8.2.3 Long production time 48

3.8.2.4 Obstacles in treating solid tumors 49

3.8.3    Opportunities 49

3.8.3.1 Untapped potential for emerging markets 49

CHAPTER 4: CAR T-CELL THERAPY, A BRIEF INTRODUCTION

4.1 OVERVIEW 50

4.2 SIXTY YEARS HISTORY OF CAR T-CELL THERAPY 51

4.3 CAR T-CELL STRUCTURE AND GENERATIONS 53

4.4 CAR T-CELL MANUFACTURING PROCESSES 56

4.5 PRICING AND PAYMENT MODELS FOR CAR T-CELL THERAPIES 59

CHAPTER 5: CAR T-CELL THERAPY MARKET, BY APPROACH TYPE

5.1 OVERVIEW 61

5.1.1    Market size and forecast 62

5.2 AUTOLOGOUS 63

5.2.1    Key market trends 63

5.2.2    Key growth factors and opportunities 64

5.2.3    Market size and forecast 64

5.2.4    Market size and forecast by country 65

5.3 ALLOGENEIC 66

5.3.1    Key market trends 67

5.3.2    Key growth factors and opportunities 68

5.3.3    Market size and forecast 68

5.3.4    Market size and forecast by country 69

CHAPTER 6: CAR T-CELL THERAPY MARKET, BY ANTIGEN TYPE

6.1 OVERVIEW 70

6.1.1         Market size and forecast 71

6.2 CD19 72

6.2.1         Market size and forecast 73

6.2.2         Market size and forecast by country 74

6.3 CD20 75

6.3.1 Market size and forecast 76

6.3.2 Market size and forecast by country 77

6.4 BCMA 78

6.4.1 Market size and forecast 79

6.4.2 Market size and forecast by country 80

6.5 MSLN 81

6.5.1 Market size and forecast 82

6.5.2 Market size and forecast by country 83

6.6 OTHERS 84

6.6.1 Market size and forecast 85

6.6.2 Market size and forecast by country 86

CHAPTER 7: CAR T-CELL THERAPY MARKET, BY APPLICATION

7.1 OVERVIEW 87

7.1.1       Market size and forecast 88

7.2 ACUTE LYMPHOBLASTIC LEUKEMIA (ALL) 89

7.2.1       Market size and forecast 90

7.2.2       Market size and forecast by country 91

7.3 DIFFUSE LARGE B-CELL LYMPHOMA (DLBCL) 92

7.3.1       Market size and forecast 93

7.3.2       Market size and forecast by country 94

7.4 MULTIPLE MYELOMA (MM) 95

7.4.1       Market size and forecast 96

7.4.2       Market size and forecast by country 97

7.5 ACUTE MYELOID LEUKEMIA (AML) 98

7.5.1       Market size and forecast 99

7.5.2       Market size and forecast by country 100

7.6 OTHERS 101

7.6.1       Market size and forecast 102

7.6.2       Market size and forecast by country 103

CHAPTER 8: CAR T-CELL THERAPY MARKET, BY REGION

8.1 OVERVIEW 104

8.1.1       Market size and forecast 104

8.2 NORTH AMERICA 105

8.2.1       Key market trends 105

8.2.2       Key growth factors and opportunities 105

8.2.3       Market size and forecast, by country 106

8.2.4       Market size and forecast, by approach type 106

8.2.5       Market size and forecast, by antigen type 107

8.2.6 Market size and forecast, by application 107

8.2.6.1 U.S. market size and forecast, by approach type 108

8.2.6.2 U.S. market size and forecast, by antigen type 108

8.2.6.3 U.S. market size and forecast, by application 109

8.2.6.4 Canada market size and forecast, by approach type 110

8.2.6.5 Canada market size and forecast, by antigen type 110

8.2.6.6 Canada market size and forecast, by application 111

8.2.6.7 Mexico market size and forecast, by approach type 112

8.2.6.8 Mexico market size and forecast, by antigen type 112

8.2.6.9 Mexico market size and forecast, by application 113

8.3 EUROPE 114

8.4.1 Key market trends 114

8.4.2 Key growth factors and opportunities 114

8.4.3 Market size and forecast, by country 115

8.4.4 Market size and forecast, by approach type 115

8.4.5 Market size and forecast, by antigen type 116

8.4.6 Market size and forecast, by application 116

8.3.6.1 UK market size and forecast, by approach type 117

8.3.6.2 UK market size and forecast, by antigen type 117

8.3.6.3 UK market size and forecast, by application 118

8.3.6.4 Germany market size and forecast, by approach type 119

8.3.6.5 Germany market size and forecast, by antigen type 119

8.3.6.6 Germany market size and forecast, by application 120

8.3.6.7 France market size and forecast, by approach type 121

8.3.6.8 France market size and forecast, by antigen type 121

8.3.6.9 France market size and forecast, by application 122

8.3.6.10 Spain market size and forecast, by approach type 123

8.3.6.11 Spain market size and forecast, by antigen type 123

8.3.6.12 Spain market size and forecast, by application 124

8.3.6.13 Italy market size and forecast, by approach type 125

8.3.6.14 Italy market size and forecast, by antigen type 125

8.3.6.15 Italy market size and forecast, by application 126

8.3.6.16 Rest of Europe market size and forecast, by approach type 127

8.3.6.17 Rest of Europe market size and forecast, by antigen type 127

8.3.6.18 Rest of Europe market size and forecast, by application 128

8.4 ASIA-PACIFIC 129

8.4.1 Key market trends 129

8.4.2 Key growth factors and opportunities 129

8.4.3 Market size and forecast, by country 130

8.4.4 Market size and forecast, by approach type 130

8.4.5       Market size and forecast, by antigen type 131

8.4.6 Market size and forecast, by application 131

8.4.6.1 China market size and forecast, by approach type 132

8.4.6.2 China market size and forecast, by antigen type 132

8.4.6.3 China market size and forecast, by application 133

8.4.6.4 Japan market size and forecast, by approach type 134

8.4.6.5 Japan market size and forecast by antigen type 134

8.4.6.6 Japan market size and forecast, by application 135

8.4.6.7 India market size and forecast, by approach type 136

8.4.6.8 India market size and forecast, by antigen type 136

8.4.6.9 India market size and forecast, by application 137

8.4.6.10 South Korea market size and forecast, by approach type 138

8.4.6.11 South Korea market size and forecast, by antigen type 138

8.4.6.12 South Korea market size and forecast, by application 139

8.4.6.13 Rest of Asia-Pacific market size and forecast, by approach type 140

8.4.6.14 Rest of Asia-Pacific market size and forecast, by antigen type 140

8.4.6.15 Rest of Asia-Pacific market size and forecast, by application 141

8.5 LAMEA 142

8.5.1 Key market trends 142

8.5.2 Key growth factors and opportunities 142

8.5.3 Market size and forecast, by country 143

8.5.4 Market size and forecast, by approach type 143

8.5.5 Market size and forecast, by antigen type 144

8.5.6 Market size and forecast, by application 144

8.5.6.1 Brazil market size and forecast by approach type 145

8.5.6.2 Brazil market size and forecast, by antigen type 145

8.5.6.3 Brazil market size and forecast, by application 146

8.5.6.4 South Africa market size and forecast, by approach type 147

8.5.6.5 South Africa market size and forecast, by antigen type 147

8.5.6.6 South Africa market size and forecast, by application 148

8.5.6.7 Rest of LAMEA market size and forecast by approach type 149

8.5.6.8 Rest of LAMEA market size and forecast, by antigen type 149

8.5.6.9 Rest of LAMEA market size and forecast, by application 150

CHAPTER 9: CLINICAL TRIALS ANALYSIS & PRODUCT PROFILES

9.1 OVERVIEW 151

9.1.1      No. of Clinical Trials from 1997 to 2019 151

9.1.2      Clinical Trials from 1997 to 2019: Based on Approach Type 152

9.1.3      Clinical Trials from 1997 to 2019: Based on Antigen Type 153

9.1.4      Clinical Trials from 1997 to 2019: Based on Application 154

9.1.5      Clinical Trials from 1997 to 2019: Based on Region 155

9.2 EXPECTED APPROVALS 156

9.3 APPROVED PRODUCTS PROFILES 157

9.3.1      KYMRIAH® 157

9.3.2      YESCARTA® 159

9.3.3      TECARTUS™ 161

CHAPTER 10: COMPANY PROFILES

10.1       Abbvie Inc. 162

10.2       Adaptimmune Therapeutics Plc 164

10.3 Allogene Therapeutics, Inc. 166

10.4 Amgen, Inc 168

10.5 Anixa Biosciences, Inc. 170

10.6 Arcellx, Inc. 172

10.7 Atara Biotherapeutics, Inc. 173

10.8 Autolus Therapeutics Plc. 175

10.9 Beam Therapeutics, Inc. 177

10.10 Bellicum Pharmaceuticals, Inc. 179

10.11 BioNtech SE 181

10.12 Bluebird Bio, Inc. 183

10.13 Carsgen Therapeutics, Ltd 185

10.14 Cartesian Therapeutics, Inc. 187

10.15 Cartherics Pty Ltd. 188

10.16 Celgene Corporation 189

10.17 Cellectis SA 191

10.18 Cellular Biomedicine Group, Inc. 193

10.19 Celularity, Inc. 195

10.20 Celyad SA 196

10.21 CRISPR Therapeutics AG 198

10.22 Eureka Therapeutics, Inc. 200

10.23 Fate Therapeutics, Inc. 201

10.24 Fortress Biotech, Inc 203

10.25 Gilead Sciences, Inc. 205

10.26 Gracell Biotechnology Ltd 207

10.27 icell Gene Therapeutics 208

10.28 Johnson & Johnson 209

10.29 Juventas Cell Therapy Ltd. 211

10.30 Kuur Therapeutics 212

10.31 Legend Biotech Corp. 213

10.32 Leucid Bio Ltd. 214

10.33 Minerva Biotechnologies Corp. 215

10.34     Molecular Medicine SPA (Molmed) 216

10.35     Nanjing Bioheng Biotech Co., Ltd. 218

10.36     Noile-Immune Biotech Inc. 219

10.37     Novartis AG 220

10.38     Oxford Biomedica PLC 222

10.39     Persongen Biotherapeutics (Suzhou) Co., Ltd. 224

10.40     Poseida Therapeutics, Inc. 226

10.41     Precigen, Inc. 227

10.42     Precision Biosciences, Inc. 229

10.43     Sorrento Therapeutics, Inc. 231

10.44     Takara Bio Inc. 233

10.45     Takeda Pharmaceutical Company Ltd. 235

10.46     TC Biopharm Ltd. 237

10.47     Tessa Therapeutics Pte Ltd. 238

10.48     Tmunity Therapeutics, Inc. 239

10.49     Unum Therapeutics Inc. 240

10.50     Xyphos Inc. 242

10.51     Ziopharm Oncology, Inc. 243

CHAPTER 11: CONCLUSION & STRATEGIC RECOMMENTATIONS

11.1     STRATEGIC RECOMMENDATIONS 245

11.2     CONCLUSION 247

CONTACT

info@biotechforecasts.com

MIKE WOOD

Marketing Executive

BIOTECH FORECASTS

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A Series of Recently Published Papers Report the Development of SARS-CoV2 Neutralizing Antibodies and Passive Immunity toward COVID19

Posted in Biomarkers: Inflammation, Coronavirus Gene Expression, COVID-19, COVID-19 effects on Human Heart, COVID-19: Pandemic Surgery Guidance, Economic Impact of Coronavirus Pandemic, Human Antibody Response, Immune Modulatory, Immune-Mediation (independent immunopathology: lung and reticuloendothelial system), Immunology, Infectious Disease & New Antibiotic Targets, number of asymptomatic infections, Population Health Management, Genetics & Pharmaceutical, SAR-Cov-2 a vasculotropic (blood vessels) RNA Virus, SARS-CoV-2, SARS-COV2 Hijacking the Complement and Coagulation Systems, Serology tests for coronavirus antibodies, Synthetic Immunology: Hacking Immune Cells, Treatment Protocols for COVID-19, Vaccinology, Viral diseases, Virology - Vector-borne DIsease, Virus Infective Acute Respiratory Syndrome: SARS-CoV, tagged anti-SARS-CoV-2 polyclonal hyperimmune globulin (H-IG), coronavirus, COVID-19, COVID-19 Treatment, humanized monoclonal antibody, neutralizing antibody, SARS-CoV-2 on May 19, 2020| Leave a Comment »

A Series of Recently Published Papers Report the Development of SARS-CoV2 Neutralizing Antibodies and Passive Immunity toward COVID19

Curator: Stephen J. Williams, Ph.D.

Passive Immunity and Treatment of Infectious Diseases

The ability of one person to pass on immunity to another person (passive immunity) is one of the chief methods we develop immunity to many antigens. For instance, maternal antibodies are passed to the offspring in the neonatal setting as well as in a mother’s milk during breast feeding. In the clinical setting this is achieved by transferring antibodies from one patient who has been exposed to an antigen (like a virus) to the another individual. However, the process of purifying the most efficacious antibody as well as its mass production is limiting due to its complexity and cost and can be prohibitively long delay during a pandemic outbreak, when therapies are few and needed immediately. Regardless, the benefits of developing neutralizing antibodies to confer passive immunity versus development of a vaccine are evident, as the former takes considerable less time than development of a safe and effective vaccine. For a good review on the development and use of neutralizing antibodies and the use of passive immunity to treat infectious diseases please read the following review:

Margaret A. Keller^1,* and E. Richard Stiehm. Passive Immunity in Prevention and Treatment of Infectious Diseases. Clin Microbiol Rev. 2000 Oct; 13(4): 602–614. doi: 10.1128/cmr.13.4.602-614.2000

ABSTRACT

Antibodies have been used for over a century in the prevention and treatment of infectious disease. They are used most commonly for the prevention of measles, hepatitis A, hepatitis B, tetanus, varicella, rabies, and vaccinia. Although their use in the treatment of bacterial infection has largely been supplanted by antibiotics, antibodies remain a critical component of the treatment of diptheria, tetanus, and botulism. High-dose intravenous immunoglobulin can be used to treat certain viral infections in immunocompromised patients (e.g., cytomegalovirus, parvovirus B19, and enterovirus infections). Antibodies may also be of value in toxic shock syndrome, Ebola virus, and refractory staphylococcal infections. Palivizumab, the first monoclonal antibody licensed (in 1998) for an infectious disease, can prevent respiratory syncytial virus infection in high-risk infants. The development and use of additional monoclonal antibodies to key epitopes of microbial pathogens may further define protective humoral responses and lead to new approaches for the prevention and treatment of infectious diseases.

TABLE 1

Summary of the efficacy of antibody in the prevention and treatment of infectious diseases

Infection
Bacterial infections
Respiratory infections (streptococcus, Streptococcus pneumoniae, Neisseria meningitis, Haemophilus influenzae)
Diphtheria
Pertussis
Tetanus
Other clostridial infections
C. botulinum
C. difficile
Staphylococcal infections
Toxic shock syndrome
Antibiotic resistance
S. epidermidis in newborns
Invasive streptococcal disease (toxic shock syndrome)
High-risk newborns
Shock, intensive care, and trauma
Pseudomonas infection
Cystic Fibrosis
Burns
Viral diseases
Hepatitis A
Hepatitis B
Hepatitis C
HIV infection
RSV infection
Herpesvirus infections
CMV
EBV
HSV
VZV
Parvovirus infection
Enterovirus infection
In newborns
Ebola
Rabies
Measles
Rubella
Mumps
Tick-borne encephalitis
Vaccinia

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A Great Explanation of Active versus Passive Immunity by Dr. John Campbell, one of the pioneers in the field of immunology:Antibodies have been used for over a century in the prevention and treatment of infectious disease. They are used most commonly for the prevention of measles, hepatitis A, hepatitis B, tetanus, varicella, rabies, and vaccinia. Although their use in the treatment of bacterial infection has largely been supplanted by antibiotics, antibodies remain a critical component of the treatment of diptheria, tetanus, and botulism. High-dose intravenous immunoglobulin can be used to treat certain viral infections in immunocompromised patients (e.g., cytomegalovirus, parvovirus B19, and enterovirus infections). Antibodies may also be of value in toxic shock syndrome, Ebola virus, and refractory staphylococcal infections. Palivizumab, the first monoclonal antibody licensed (in 1998) for an infectious disease, can prevent respiratory syncytial virus infection in high-risk infants. The development and use of additional monoclonal antibodies to key epitopes of microbial pathogens may further define protective humoral responses and lead to new approaches for the prevention and treatment of infectious diseases.

However, developing successful neutralizing antibodies can still be difficult but with the latest monoclonal antibody technology, as highlighted by the following papers, this process has made much more efficient. In addition, it is not feasable to isolate antibodies from the plasma of covalescent patients in a scale that is needed for a worldwide outbreak.

A good explanation of the need can be found is Dr. Irina Robu’s post Race to develop antibody drugs for COVID-19 where:

When fighting off foreign invaders, our bodies make antibodies precisely produced for the task. The reason vaccines offer such long-lasting protection is they train the immune system to identify a pathogen, so immune cells remember and are ready to attack the virus when it appears. Monoclonal antibodies for coronavirus would take the place of the ones our bodies might produce to fight the disease. The manufactured antibodies would be infused into the body to either tamp down an existing infection, or to protect someone who has been exposed to the virus. However, these drugs are synthetic versions of the convalescent plasma treatments that rely on antibodies from people who have recovered from infection. But the engineered versions are easier to scale because they’re manufactured in rats, rather than from plasma donors.

The following papers represent the latest published work on development of therapeutic and prophylactic neutralizing antibodies to the coronavirus SARS-CoV2

1. Cross-neutralization of SARS-CoV-2 by a human monoclonal SARS-CoV antibody.

Pinto, D., Park, Y., Beltramello, M. et al. Cross-neutralization of SARS-CoV-2 by a human monoclonal SARS-CoV antibody. Nature (2020). https://doi.org/10.1038/s41586-020-2349-y

Abstract

SARS-CoV-2 is a newly emerged coronavirus responsible for the current COVID-19 pandemic that has resulted in more than 3.7 million infections and 260,000 deaths as of 6 May 2020^1,2. Vaccine and therapeutic discovery efforts are paramount to curb the pandemic spread of this zoonotic virus. The SARS-CoV-2 spike (S) glycoprotein promotes entry into host cells and is the main target of neutralizing antibodies. Here we describe multiple monoclonal antibodies targeting SARS-CoV-2 S identified from memory B cells of an individual who was infected with SARS-CoV in 2003. One antibody, named S309, potently neutralizes SARS-CoV-2 and SARS-CoV pseudoviruses as well as authentic SARS-CoV-2 by engaging the S receptor-binding domain. Using cryo-electron microscopy and binding assays, we show that S309 recognizes a glycan-containing epitope that is conserved within the sarbecovirus subgenus, without competing with receptor attachment. Antibody cocktails including S309 along with other antibodies identified here further enhanced SARS-CoV-2 neutralization and may limit the emergence of neutralization-escape mutants. These results pave the way for using S309- and S309-containing antibody cocktails for prophylaxis in individuals at high risk of exposure or as a post-exposure therapy to limit or treat severe disease.

2. Potent neutralizing antibodies against SARS-CoV-2 identified by high-throughput single-cell sequencing of convalescent patients’ B cells

Yunlong Cao et al. Potent neutralizing antibodies against SARS-CoV-2 identified by high-throughput single-cell sequencing of convalescent patients’ B cells. Cell (2020).

https://doi.org/10.1016/j.cell.2020.05.025

Summary

The COVID-19 pandemic urgently needs therapeutic and prophylactic interventions. Here we report the rapid identification of SARS-CoV-2 neutralizing antibodies by high-throughput single-cell RNA and VDJ sequencing of antigen-enriched B cells from 60 convalescent patients. From 8,558 antigen-binding IgG1⁺ clonotypes, 14 potent neutralizing antibodies were identified with the most potent one, BD-368-2, exhibiting an IC₅₀ of 1.2 ng/mL and 15 ng/mL against pseudotyped and authentic SARS-CoV-2, respectively. BD-368-2 also displayed strong therapeutic and prophylactic efficacy in SARS-CoV-2-infected hACE2-transgenic mice. Additionally, the 3.8Å Cryo-EM structure of a neutralizing antibody in complex with the spike-ectodomain trimer revealed the antibody’s epitope overlaps with the ACE2 binding site. Moreover, we demonstrated that SARS-CoV-2 neutralizing antibodies could be directly selected based on similarities of their predicted CDR3_H structures to those of SARS-CoV neutralizing antibodies. Altogether, we showed that human neutralizing antibodies could be efficiently discovered by high-throughput single B-cell sequencing in response to pandemic infectious diseases.

3. A human monoclonal antibody blocking SARS-CoV-2 infection

Wang, C., Li, W., Drabek, D. et al. A human monoclonal antibody blocking SARS-CoV-2 infection. Nat Commun 11, 2251 (2020). https://doi.org/10.1038/s41467-020-16256-y

Abstract

The emergence of the novel human coronavirus SARS-CoV-2 in Wuhan, China has caused a worldwide epidemic of respiratory disease (COVID-19). Vaccines and targeted therapeutics for treatment of this disease are currently lacking. Here we report a human monoclonal antibody that neutralizes SARS-CoV-2 (and SARS-CoV) in cell culture. This cross-neutralizing antibody targets a communal epitope on these viruses and may offer potential for prevention and treatment of COVID-19.

Extra References on Development of Neutralizing antibodies for COVID19 {Sars-CoV2} published this year (2020) [1-4]

Fan P, Chi X, Liu G, Zhang G, Chen Z, Liu Y, Fang T, Li J, Banadyga L, He S et al: Potent neutralizing monoclonal antibodies against Ebola virus isolated from vaccinated donors. mAbs 2020, 12(1):1742457.
Dussupt V, Sankhala RS, Gromowski GD, Donofrio G, De La Barrera RA, Larocca RA, Zaky W, Mendez-Rivera L, Choe M, Davidson E et al: Potent Zika and dengue cross-neutralizing antibodies induced by Zika vaccination in a dengue-experienced donor. Nature medicine 2020, 26(2):228-235.
Young CL, Lyons AC, Hsu WW, Vanlandingham DL, Park SL, Bilyeu AN, Ayers VB, Hettenbach SM, Zelenka AM, Cool KR et al: Protection of swine by potent neutralizing anti-Japanese encephalitis virus monoclonal antibodies derived from vaccination. Antiviral research 2020, 174:104675.
Sautto GA, Kirchenbaum GA, Abreu RB, Ecker JW, Pierce SR, Kleanthous H, Ross TM: A Computationally Optimized Broadly Reactive Antigen Subtype-Specific Influenza Vaccine Strategy Elicits Unique Potent Broadly Neutralizing Antibodies against Hemagglutinin. J Immunol 2020, 204(2):375-385.

For More Articles on COVID-19 Please see Our Coronavirus Portal on this Open Access Scientific Journal at:

https://pharmaceuticalintelligence.com/coronavirus-portal/

and the following Articles on Immunity at

Race to develop antibody drugs for COVID-19

Bispecific and Trispecific Engagers: NK-T Cells and Cancer Therapy

Issues Need to be Resolved With ImmunoModulatory Therapies: NK cells, mAbs, and adoptive T cells

Antibody-bound Viral Antigens

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Impaired antibody development is promoted by chronic viral infection

Posted in Adaptive Immune Response to Biomaterials and Tissue Repair, Allergy and Infectious Diseases, Antibody Responses Predict Antigen Exposure, Autoimmune Inflammatory DIseases, “Antibody–enzyme conjugates”, Biotechnology, Cell Biology, Cell Biology, Signaling & Cell Circuits, Cell Processing System in Cell Therapy Process Development, combination immunotherapies., Diagnostic Immunology, Human Antibody Response, Human Circulating Antibody Repertoire, Human Immune System in Health and in Disease, Human Naive B Cell Repertoire, Immune Engineering, Immune Modulatory, Immuno-Oncology & Genomics, Immunodiagnostics, Immunology, Immunotherapy, Infectious Disease & New Antibiotic Targets, Infectious Disease Immunodiagnostics, Innovation in Immunology Diagnostics, Monoclonal antibody therapy, Monoclonal Immunotherapy, Protection Against Autoimmune Disease, Signaling & Cell Circuits, Synergistic Innate and Adaptive Immunotherapy, Synthetic Immunology: Hacking Immune Cells, Universal Immune Cell Therapies (uICT), Viral diseases, tagged Antibody, B-cell, chronic infection, germinal centre, viral infection on December 1, 2019| Leave a Comment »

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

Effective humoral immune responses to infection and immunization are defined by high-affinity antibodies generated as a result of B cell differentiation and selection that occurs within germinal centers (GC). Within the GC, B cells undergo affinity maturation, an iterative and competitive process wherein B cells mutate their immunoglobulin genes (somatic hypermutation) and undergo clonal selection by competing for T cell help. Balancing the decision to remain within the GC and continue participating in affinity maturation or to exit the GC as a plasma cell (PC) or memory B cell (MBC) is critical for achieving optimal antibody avidity, antibody quantity, and establishing immunological memory in response to immunization or infection. Humoral immune responses during chronic infections are often dysregulated and characterized by hypergammaglobulinemia, decreased affinity maturation, and delayed development of neutralizing antibodies. Previous studies have suggested that poor antibody quality is in part due to deletion of B cells prior to establishment of the GC response.

In fact the impact of chronic infections on B cell fate decisions in the GC remains poorly understood. To address this question, researchers used single-cell transcriptional profiling of virus-specific GC B cells to test the hypothesis that chronic viral infection disrupted GC B cell fate decisions leading to suboptimal humoral immunity. These studies revealed a critical GC differentiation checkpoint that is disrupted by chronic infection, specifically at the point of dark zone re-entry. During chronic viral infection, virus-specific GC B cells were shunted towards terminal plasma cell (PC) or memory B cell (MBC) fates at the expense of continued participation in the GC. Early GC exit was associated with decreased B cell mutational burden and antibody quality. Persisting antigen and inflammation independently drove facets of dysregulation, with a key role for inflammation in directing premature terminal GC B cell differentiation and GC exit. Thus, the present research defines GC defects during chronic viral infection and identify a critical GC checkpoint that is short-circuited, preventing optimal maturation of humoral immunity.

Together, these studies identify a key GC B cell differentiation checkpoint that is dysregulated during chronic infection. Further, it was found that the chronic inflammatory environment, rather than persistent antigen, is sufficient to drive altered GC B cell differentiation during chronic infection even against unrelated antigens. However, the data also indicate that inflammatory circuits are likely linked to perception of antigen stimulation. Nevertheless, this study reveals a B cell-intrinsic program of transcriptional skewing in chronic viral infection that results in shunting out of the cyclic GC B cell process and early GC exit with consequences for antibody quality and hypergammaglobulinemia. These findings have implications for vaccination in individuals with pre-existing chronic infections where antibody responses are often ineffective and suggest that modulation of inflammatory pathways may be therapeutically useful to overcome impaired humoral immunity and foster affinity maturation during chronic viral infections.

References:

https://www.biorxiv.org/content/10.1101/849844v1

https://www.ncbi.nlm.nih.gov/pubmed/25656706

https://www.ncbi.nlm.nih.gov/pubmed/27653600

https://www.ncbi.nlm.nih.gov/pubmed/26912368

https://www.ncbi.nlm.nih.gov/pubmed/26799208

https://www.ncbi.nlm.nih.gov/pubmed/23001146

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Newly Found Functions of B Cell

Posted in Adaptive Immune Response to Biomaterials and Tissue Repair, Allergy and Infectious Diseases, Autoimmune Inflammatory DIseases, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Vaccines: Targeting Cancer Genes for Immunotherapy, Cancer-Immune Interactions, CNS-Immune Interface, combination immunotherapies., Cytokine Receptor Structure, Cytokines, Diagnostic Immunology, Human Immune System in Health and in Disease, Human Naive B Cell Repertoire, Immune Engineering, Immune Modulatory, Immuno-Oncology & Genomics, Immunodiagnostics, Immunology, Immunotherapy, Infectious Disease Immunodiagnostics, Innovation in Immunology Diagnostics, Integrin-targeted Combination Immunotherapy, Metabolic Immuno-Oncology, Modulating Macrophages in Cancer Immunotherapy, Monoclonal Immunotherapy, NK Cell-Based Cancer Immunotherapy, Protection Against Autoimmune Disease, Synergistic Innate and Adaptive Immunotherapy, Synthetic Immunology: Hacking Immune Cells, Tolerance-inducing Autoimmune Disease Therapeutics, Universal Immune Cell Therapies (uICT), tagged Allergy, autoimmunity, B cell receptor, B-cell, Cancer, immune system, immunosuppression on May 23, 2019| Leave a Comment »

Newly Found Functions of B Cell

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

4.1.8

4.1.8 Newly Found Functions of B Cell, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 4: Single Cell Genomics

The importance of B cells to human health is more than what is already known. Vaccines capable of eradicating disease activate B cells, cancer checkpoint blockade therapies are produced using B cells, and B cell deficiencies have devastating impacts. B cells have been a subject of fascination since at least the 1800s. The notion of a humoral branch to immunity emerged from the work of and contemporaries studying B cells in the early 1900s.

Efforts to understand how we could make antibodies from B cells against almost any foreign surface while usually avoiding making them against self, led to Burnet’s clonal selection theory. This was followed by the molecular definition of how a diversity of immunoglobulins can arise by gene rearrangement in developing B cells. Recombination activating gene (RAG)-dependent processes of V-(D)-J rearrangement of immunoglobulin (Ig) gene segments in developing B cells are now known to be able to generate an enormous amount of antibody diversity (theoretically at least 1016 possible variants).

With so much already known, B cell biology might be considered ‘‘done’’ with only incremental advances still to be made, but instead, there is great activity in the field today with numerous major challenges that remain. For example, efforts are underway to develop vaccines that induce broadly neutralizing antibody responses, to understand how autoantigen- and allergen-reactive antibodies arise, and to harness B cell-depletion therapies to correct non-autoantibody-mediated diseases, making it evident that there is still an enormous amount we do not know about B cells and much work to be done.

Multiple self-tolerance checkpoints exist to remove autoreactive specificities from the B cell repertoire or to limit the ability of such cells to secrete autoantigen-binding antibody. These include receptor editing and deletion in immature B cells, competitive elimination of chronically autoantigen binding B cells in the periphery, and a state of anergy that disfavors PC (plasma cell) differentiation. Autoantibody production can occur due to failures in these checkpoints or in T cell self-tolerance mechanisms. Variants in multiple genes are implicated in increasing the likelihood of checkpoint failure and of autoantibody production occurring.

Autoantibodies are pathogenic in a number of human diseases including SLE (Systemic lupus erythematosus), pemphigus vulgaris, Grave’s disease, and myasthenia gravis. B cell depletion therapy using anti-CD20 antibody has been protective in some of these diseases such as pemphigus vulgaris, but not others such as SLE and this appears to reflect the contribution of SLPC (Short lived plasma cells) versus LLPC (Long lived plasma cells) to autoantibody production and the inability of even prolonged anti-CD20 treatment to eliminate the later. These clinical findings have added to the importance of understanding what factors drive SLPC versus LLPC development and what the requirements are to support LLPCs.

B cell depletion therapy has also been efficacious in several other autoimmune diseases, including multiple sclerosis (MS), type 1 diabetes, and rheumatoid arthritis (RA). While the potential contributions of autoantibodies to the pathology of these diseases are still being explored, autoantigen presentation has been posited as another mechanism for B cell disease-promoting activity.

In addition to autoimmunity, B cells play an important role in allergic diseases. IgE antibodies specific for allergen components sensitize mast cells and basophils for rapid degranulation in response to allergen exposures at various sites, such as in the intestine (food allergy), nose (allergic rhinitis), and lung (allergic asthma). IgE production may thus be favored under conditions that induce weak B cell responses and minimal GC (Germinal center) activity, thereby enabling IgE+ B cells and/or PCs to avoid being outcompeted by IgG+ cells. Aside from IgE antibodies, B cells may also contribute to allergic inflammation through their interactions with T cells.

B cells have also emerged as an important source of the immunosuppressive cytokine IL-10. Mouse studies revealed that B cell-derived IL-10 can promote recovery from EAE (Experimental autoimmune encephalomyelitis) and can be protective in models of RA and type 1 diabetes. Moreover, IL-10 production from B cells restrains T cell responses during some viral and bacterial infections. These findings indicate that the influence of B cells on the cytokine milieu will be context dependent.

The presence of B cells in a variety of solid tumor types, including breast cancer, ovarian cancer, and melanoma, has been associated in some studies with a positive prognosis. The mechanism involved is unclear but could include antigen presentation to CD4 and CD8 T cells, antibody production and subsequent enhancement of presentation, or by promoting tertiary lymphoid tissue formation and local T cell accumulation. It is also noteworthy that B cells frequently make antibody responses to cancer antigens and this has led to efforts to use antibodies from cancer patients as biomarkers of disease and to identify immunotherapy targets.

Malignancies of B cells themselves are a common form of hematopoietic cancer. This predilection arises because the gene modifications that B cells undergo during development and in immune responses are not perfect in their fidelity, and antibody responses require extensive B cell proliferation. The study of B cell lymphomas and their associated genetic derangements continues to be illuminating about requirements for normal B cell differentiation and signaling while also leading to the development of targeted therapies.

Overall this study attempted to capture some of the advances in the understanding of B cell biology that have occurred since the turn of the century. These include important steps forward in understanding how B cells encounter antigens, the co-stimulatory and cytokine requirements for their proliferation and differentiation, and how properties of the B cell receptor, the antigen, and helper T cells influence B cell responses. Many advances continue to transform the field including the impact of deep sequencing technologies on understanding B cell repertoires, the IgA-inducing microbiome, and the genetic defects in humans that compromise or exaggerate B cell responses or give rise to B cell malignancies.

Other advances that are providing insight include:

single-cell approaches to define B cell heterogeneity,
glycomic approaches to study effector sugars on antibodies,
new methods to study human B cell responses including CRISPR-based manipulation, and
the use of systems biology to study changes at the whole organism level.

With the recognition that B cells and antibodies are involved in most types of immune response and the realization that inflammatory processes contribute to a wider range of diseases than previously believed, including, for example, metabolic syndrome and neurodegeneration, it is expected that further

basic research-driven discovery about B cell biology will lead to more and improved approaches to maintain health and fight disease in the future.

References:

https://www.cell.com/cell/fulltext/S0092-8674(19)30278-8

https://onlinelibrary.wiley.com/doi/full/10.1002/hon.2405

https://www.pnas.org/content/115/18/4743

https://onlinelibrary.wiley.com/doi/full/10.1111/all.12911

https://cshperspectives.cshlp.org/content/10/5/a028795

https://www.sciencedirect.com/science/article/abs/pii/S0049017218304955

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CytoReason is re-defining the Context of the Immune System for Drug Discovery

Posted in Adaptive Immune Response to Biomaterials and Tissue Repair, BioTechnology - Venture Creation, Engineering Better T Cells, Immune Engineering, Immune Modulatory, Immunodiagnostics, Immunotherapy, NK Cell-Based Cancer Immunotherapy, Protection Against Autoimmune Disease, Synergistic Innate and Adaptive Immunotherapy on May 21, 2019| Leave a Comment »

CytoReason is re-defining the Context of the Immune System for Drug Discovery

Reporter: Aviva Lev-Ari, PhD, RN

CytoReason is re-defining the context of the immune system at a cellular level in order to better understand disease and support more effective drug discovery and development.

Our leading-edge machine-learning driven approach identifies “cause and effect” of the gene/cell/cytokine relationships that lie at the heart of treating disease.

Faster and more accurately than ever before.

CytoReason’s mission is to simulate the cells that can stimulate discovery of:

New targets for treating disease

New insights to mechanism of actions (both of disease and drugs)

Differences in responses to both disease and treatment

Which diseases a drug can impact

We have developed a unique machine-learning driven approach to “seeing” the cells that can make the difference in patients seeing a better life.

The insights our approach generates, enable pharmaceutical and biotech companies to make the right decisions, at the right time, in the drug discovery and development programs that bring better therapies.

Based on cutting edge technologies, trained on data that would normally be impossible to access, and steered by leading biological and data science researchers, our approach is underpinned by three core principles:

SOURCE

https://www.cytoreason.com/

Press Release

https://docs.wixstatic.com/ugd/216dd2_b715f2c29a8c496eb65315d332a7077e.pdf

Case Studies

Click one of the buttons below to view a short case study presention:

IBD: Anti-TNFα Pre-Treatment Response

Atopic Dermatitis: IL4 MoA

Melanoma: Target & Biomarker ID

Collaboration & Results

Working with leading global pharma and biotech companies and key research institutions, our results help guide R&D decision making.

Results

Our platform is tried and tested, producing real results with validation

•    Discovered: New cellular players in melanoma microenvironment

•   Discovered: New IL4 mechanism of action in atopic dermatitis

•   Discovered: Novel pre-treatment biomarkers in IBD anti-TNFα therapy

•   Discovered: 355 previously unreported cell/cytokine interactions (view infographic)

Publications

Science is the backbone of our methodologies and applications, and must stand the test of scientific scrutiny. To date we have 16 research papers published in top quality peer-reviewed scientific journals, including four in 2018 alone – 3 of which were published in journals from the Nature group

Click here to see our publications

SOURCE

https://www.cytoreason.com/

Shen-Orr told Forbes in an article published late last month that CytoReason’s tech is able to calculate immune age in one of two ways: “Via cell-subset composition nearest neighbor approach or based on a gene expression signature where the genes are predictive of the cell-subsets composition, and they test for their enrichment in the gene expression pattern of the sample. The immune profiles of individuals are used to predict immune changes based on a machine learning methodology deployed on data on a range of cell-subsets. ”

“The immune age is a biological clock that will help to identify, the decline and progress in immunity that occurs in old age, to determine preventive measures and develop new treatment modalities to minimize chronic disease and death,” he added.

CytoReason’s tech has so far yielded two pending patents, 10 commercial and scientific collaborations, and 16 peer-reviewed publications.

Harel says it was a combination of forces that made CytoReason’s immune-focused methodology work: Big Data, machine learning, and biology. He describes it as “the intersection of computer science and biology.”

SEE ALSO: The Future Of Medicine: Israeli Scientists Unveil New Tech To 3D-Print Personalized Drugs

Professor Magdassi tells NoCamels that with 3D printing of hydrogels, molecules that are soluble in water, scientists can improve the performance of the drug through its delivery. For example, “the hydrogel once ingested can be designed to swell, releasing two, or three, or four drugs at a time [or with a delay] or it can be designed not to swell, depending on what we are trying to achieve.”

“The drug can be tailored to the patient because of the unique shape or structure of the hydrogel and/or its release behavior,” Professor Magdassi explains.

Currently, there is one 3D-printed drug on the market. In 2015, the US Food and Drug Administration (FDA) approved Spritam, a 3D-printed powdered drug in pill form for the treatment of epileptic seizures, designed to dissolve faster than other pills.

SOURCE

http://nocamels.com/2018/11/future-medicine-israel-3d-print-personalized-drugs/

Quantifying The Age Of Our Immune System Could Bring Us Some Steps Closer To Precision Medicine

Yiannis Mouratidis

Contributor

Science

Last January, CytoReason announced an agreement with Pfizer, in which the latter will leverage the former’s technology to create cell-based models of the immune system. According to the agreement, CytoReason will receive an undisclosed amount in the low double-digit millions of U.S. dollars from Pfizer in access fees, research support and success-based payments. Prof. Shen-Orr concluded, “The immune age is a biological clock that will help to identify, the decline and progress in immunity that occurs in old age, to determine preventive measures and develop new treatment modalities to minimize chronic disease and death.”

SOURCE

https://www.forbes.com/sites/yiannismouratidis/2019/04/29/quantifying-the-age-of-our-immune-system-could-bring-us-some-steps-closer-to-precision-medicine/#15ef4e0628b3

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Immunoediting can be a constant defense in the cancer landscape

Posted in Anticancer Resistance, Apoptosis, BioIT: BioInformatics, NGS, Clinical & Translational, Pharmaceutical R&D Informatics, Clinical Genomics, Cancer Informatics, Breast Cancer - impalpable breast lesions, Cancer - General, Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Genomics, Cancer Informatics, cancer metabolism, Cancer Prevention: Research & Programs, Cancer Screening, Cancer Surgery of the Heart, Cancer Vaccines: Targeting Cancer Genes for Immunotherapy, Cancer-Immune Interactions, Cell Biology, Cell Biology, Signaling & Cell Circuits, Cell death pathways, Cell Processing System in Cell Therapy Process Development, cell-based therapy, Childhood cancer, Circulating Tumor Cells (CTC), combination immunotherapies., Efficacy of Anti-Tumor T Cells, Engineering Better T Cells, Engineering Enhanced Cancer Vaccines, Funding Opportunities for Cancer Research, Human Immune System in Health and in Disease, Imaging-based Cancer Patient Management, Immune Modulatory, Immuno-Oncology & Genomics, Immunology, Immunotherapy, Infectious Disease Immunodiagnostics, Innovation in Immunology Diagnostics, Integrin-targeted Combination Immunotherapy, Liquid Biopsy Chip detects an array of metastatic cancer cell markers in blood, Liquid Biopsy: Circulating Tumor Cells in Urine and Blood, Metabolic Immuno-Oncology, Microbiome and Responses to Cancer Therapy, MicroEngineering Cell-Tissue & Systems, Modulating Macrophages in Cancer Immunotherapy, Monoclonal Immunotherapy, NK Cell-Based Cancer Immunotherapy, Pancreatic cancer, Pharmacotherapy and Cell Activity, Population Health Management, Population Health Management, Genetics & Pharmaceutical, Population Health Management, Nutrition and Phytochemistry, Precision Cancer Medicine, Prostate Cancer: Monitoring vs Treatment, RNA Biology, Cancer and Therapeutics, Signaling & Cell Circuits, Single Cell Genomics, stem cell biology and patient-specific, Stem Cells for Regenerative Medicine, Synergistic Innate and Adaptive Immunotherapy, Synthetic Immunology: Hacking Immune Cells, Universal Immune Cell Therapies (uICT), Voices of Patients and Healthcare Providers, tagged Cancer, cancer vaccine, DNA, HLA, immunoediting on March 16, 2019| Leave a Comment »

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

There are many considerations in the cancer immunoediting landscape of defense and regulation in the cancer hallmark biology. The cancer hallmark biology in concert with key controls of the HLA compatibility affinity mechanisms are pivotal in architecting a unique patient-centric therapeutic application. Selection of random immune products including neoantigens, antigens, antibodies and other vital immune elements creates a high level of uncertainty and risk of undesirable immune reactions. Immunoediting is a constant process. The human innate and adaptive forces can either trigger favorable or unfavorable immunoediting features. Cancer is a multi-disease entity. There are multi-factorial initiators in a certain disease process. Namely, environmental exposures, viral and / or microbiome exposure disequilibrium, direct harm to DNA, poor immune adaptability, inherent risk and an individual’s own vibration rhythm in life.

When a human single cell is crippled (Deranged DNA) with mixed up molecular behavior that is the initiator of the problem. A once normal cell now transitioned into full threatening molecular time bomb. In the modeling and creation of a tumor it all begins with the singular molecular crisis and crippling of a normal human cell. At this point it is either chop suey (mixed bit responses) or a productive defensive and regulation response and posture of the immune system. Mixed bits of normal DNA, cancer-laden DNA, circulating tumor DNA, circulating normal cells, circulating tumor cells, circulating immune defense cells, circulating immune inflammatory cells forming a moiety of normal and a moiety of mess. The challenge is to scavenge the mess and amplify the normal.

Immunoediting is a primary push-button feature that is definitely required to be hit when it comes to initiating immune defenses against cancer and an adaptation in favor of regression. As mentioned before that the tumor microenvironment is a “mixed bit” moiety, which includes elements of the immune system that can defend against circulating cancer cells and tumor growth. Personalized (Precision-Based) cancer vaccines must become the primary form of treatment in this case. Current treatment regimens in conventional therapy destroy immune defenses and regulation and create more serious complications observed in tumor progression, metastasis and survival. Commonly resistance to chemotherapeutic agents is observed. These personalized treatments will be developed in concert with cancer hallmark analytics and immunocentrics affinity and selection mapping. This mapping will demonstrate molecular pathway interface and HLA compatibility and adaptation with patientcentricity.

References:

https://www.linkedin.com/pulse/immunoediting-cancer-landscape-john-catanzaro/

https://www.cell.com/cell/fulltext/S0092-8674(16)31609-9

https://www.researchgate.net/publication/309432057_Circulating_tumor_cell_clusters_What_we_know_and_what_we_expect_Review

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4190561/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5840207/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5593672/

https://www.frontiersin.org/articles/10.3389/fimmu.2018.00414/full

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5593672/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4190561/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4388310/

https://www.linkedin.com/pulse/cancer-hallmark-analytics-omics-data-pathway-studio-review-catanzaro/

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Immunotherapy may help in glioblastoma survival

Posted in Anticancer Resistance, BioIT: BioInformatics, NGS, Clinical & Translational, Pharmaceutical R&D Informatics, Clinical Genomics, Cancer Informatics, Breast Cancer - impalpable breast lesions, Cancer - General, Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Genomics, Cancer Informatics, cancer metabolism, Cancer Prevention: Research & Programs, Cancer Screening, Cancer Vaccines: Targeting Cancer Genes for Immunotherapy, Cancer-Immune Interactions, Cell Biology, Childhood cancer, CNS-Immune Interface, combination immunotherapies., Efficacy of Anti-Tumor T Cells, Engineering Better T Cells, Glioblastoma, Imaging-based Cancer Patient Management, Immune Engineering, Immune Modulatory, Immuno-Oncology & Genomics, Immunodiagnostics, Immunology, Immunotherapy, Inflammasome, Innovation in Immunology Diagnostics, Integrin-targeted Combination Immunotherapy, Liquid Biopsy Chip detects an array of metastatic cancer cell markers in blood, Metabolic Immuno-Oncology, Metastasis Process, Modulating Macrophages in Cancer Immunotherapy, Monoclonal Immunotherapy, Neuronal Circuits, NK Cell-Based Cancer Immunotherapy, Pancreatic cancer, Population genetics, Population Health Management, Population Health Management, Genetics & Pharmaceutical, Precision Cancer Medicine, Prostate Cancer: Monitoring vs Treatment, RNA Biology, Cancer and Therapeutics, Synergistic Innate and Adaptive Immunotherapy, Synthetic Immunology: Hacking Immune Cells, Universal Immune Cell Therapies (uICT), tagged Cancer, Glioblastoma, Immunotherapy, pembrolizumab, survival, Therapy on March 16, 2019| Leave a Comment »

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

Glioblastoma is the most common primary malignant brain tumor in adults and is associated with poor survival. But, in a glimmer of hope, a recent study found that a drug designed to unleash the immune system helped some patients live longer. Glioblastoma powerfully suppresses the immune system, both at the site of the cancer and throughout the body, which has made it difficult to find effective treatments. Such tumors are complex and differ widely in their behavior and characteristics.

A small randomized, multi-institution clinical trial was conducted and led by researchers at the University of California at Los Angeles involved patients who had a recurrence of glioblastoma, the most common central nervous system cancer. The aim was to evaluate immune responses and survival following neoadjuvant and/or adjuvant therapy with pembrolizumab (checkpoint inhibitor) in 35 patients with recurrent, surgically resectable glioblastoma. Patients who were randomized to receive neoadjuvant pembrolizumab, with continued adjuvant therapy following surgery, had significantly extended overall survival compared to patients that were randomized to receive adjuvant, post-surgical programmed cell death protein 1 (PD-1) blockade alone.

Neoadjuvant PD-1 blockade was associated with upregulation of T cell– and interferon-γ-related gene expression, but downregulation of cell-cycle-related gene expression within the tumor, which was not seen in patients that received adjuvant therapy alone. Focal induction of programmed death-ligand 1 in the tumor microenvironment, enhanced clonal expansion of T cells, decreased PD-1 expression on peripheral blood T cells and a decreasing monocytic population was observed more frequently in the neoadjuvant group than in patients treated only in the adjuvant setting. These findings suggest that the neoadjuvant administration of PD-1 blockade enhanced both the local and systemic antitumor immune response and may represent a more efficacious approach to the treatment of this uniformly lethal brain tumor.

Immunotherapy has not proved to be effective against glioblastoma. This small clinical trial explored the effect of PD-1 blockade on recurrent glioblastoma in relation to the timing of administration. A total of 35 patients undergoing resection of recurrent disease were randomized to either neoadjuvant or adjuvant pembrolizumab, and surgical specimens were compared between the two groups. Interestingly, the tumoral gene expression signature varied between the two groups, such that those who received neoadjuvant pembrolizumab displayed an INF-γ gene signature suggestive of T-cell activation as well as suppression of cell-cycle signaling, possibly consistent with growth arrest. Although the study was not powered for efficacy, the group found an increase in overall survival in patients receiving neoadjuvant pembrolizumab compared with adjuvant pembrolizumab of 13.7 months versus 7.5 months, respectively.

In this small pilot study, neoadjuvant PD-1 blockade followed by surgical resection was associated with intratumoral T-cell activation and inhibition of tumor growth as well as longer survival. How the drug works in glioblastoma has not been totally established. The researchers speculated that giving the drug before surgery prompted T-cells within the tumor, which had been impaired, to attack the cancer and extend lives. The drug didn’t spur such anti-cancer activity after the surgery because those T-cells were removed along with the tumor. The results are very important and very promising but would need to be validated in much larger trials.

References:

https://www.washingtonpost.com/health/2019/02/11/immunotherapy-may-help-patients-with-kind-cancer-that-killed-john-mccain/?noredirect=on&utm_term=.e1b2e6fffccc

https://www.ncbi.nlm.nih.gov/pubmed/30742122

https://www.practiceupdate.com/content/neoadjuvant-anti-pd-1-immunotherapy-promotes-immune-responses-in-recurrent-gbm/79742/37/12/1

https://www.esmo.org/Oncology-News/Neoadjuvant-PD-1-Blockade-in-Glioblastoma

https://neurosciencenews.com/immunotherapy-glioblastoma-cancer-10722/

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TWEETS by @pharma_BI and @AVIVA1950 at #IESYMPOSIUM – @kochinstitute 2019 #Immune #Engineering #Symposium, 1/28/2019 – 1/29/2019

Posted in Adaptive Immune Response to Biomaterials and Tissue Repair, Antibody Responses Predict Antigen Exposure, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer-Immune Interactions, CAR-T, combination immunotherapies., Conference Coverage with Social Media, CRISPR/Cas9 & Gene Editing, Cytokine Receptor Structure, Efficacy of Anti-Tumor T Cells, Engineering Better T Cells, Human Antibody Response, Human Circulating Antibody Repertoire, Human Naive B Cell Repertoire, Immune Engineering, Immune Modulatory, Immuno-Oncology & Genomics, Immunodiagnostics, Immunology, Immunotherapy, Integrin-targeted Combination Immunotherapy, MHC Repertoires for Antigen Prediction, Modulating Macrophages in Cancer Immunotherapy, mRNA platform in Drug DIscovery, NK Cell-Based Cancer Immunotherapy, Protection Against Autoimmune Disease, Synergistic Innate and Adaptive Immunotherapy, Synthetic Immunology: Hacking Immune Cells on January 31, 2019| Leave a Comment »

TWEETS by @pharma_BI and @AVIVA1950 at #IESYMPOSIUM – @kochinstitute 2019 #Immune #Engineering #Symposium, 1/28/2019 – 1/29/2019

Real Time Press Coverage: Aviva Lev-Ari, PhD, RN

2.1.3.4 TWEETS by @pharma_BI and @AVIVA1950 at #IESYMPOSIUM – @kochinstitute 2019 #Immune #Engineering #Symposium, 1/28/2019 – 1/29/2019, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair

eProceedings for Day 1 and Day 2

LIVE Day One – Koch Institute 2019 Immune Engineering Symposium, January 28, 2019, Kresge Auditorium, MIT

https://pharmaceuticalintelligence.com/2019/01/28/live-day-one-koch-institute-2019-immune-engineering-symposium-january-28-2019-kresge-auditorium-mit/

LIVE Day Two – Koch Institute 2019 Immune Engineering Symposium, January 29, 2019, Kresge Auditorium, MIT

https://pharmaceuticalintelligence.com/2019/01/29/live-day-two-koch-institute-2019-immune-engineering-symposium-january-29-2019-kresge-auditorium-mit/

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AMAZING Conference I covered in Real Time #Immune #Engineering
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AMAZING Conference I covered in Real Time

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LIVE Day One – e-Proceedings #IESYMPOSIUM @pharma_BI @AVIVA1950 @KochInstitute 2019 #Immune #Engineering #Symposium, January 28, 2019, Kresge Auditorium, MIT https://pharmaceuticalintelligence.com/2019/01/28/live-day-one-koch-institute-2019-immune-engineering-symposium-january-28-2019-kresge-auditorium-mit/ … via @Pharma_BI

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LIVE Day Two – Koch Institute 2019 Immune Engineering Symposium, January 29, 2019, Kresge Auditorium, MIT http://pharmaceuticalintelligence.com/2019/01/29/live-day-two-koch-institute-2019-immune-engineering-symposium-january-29-2019-kresge-auditorium-mit/ …

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#IESYMPOSIUM @pharma_BI @AVIVA1950 Aviv Regev @kochinstitute Melanoma: malignant cells with resistance in cold niches in situ cells express the resistance program pre-treatment: resistance UP – cold Predict checkpoint immunotherapy outcomes CDK4/6 abemaciclib in cell lines
Aviva Lev-Ari‏ @AVIVA1950 7 hours ago

#IESYMPOSIUM @pharma_BI @AVIVA1950 Aviv Regev, @broadinstitute @kochinstitute #Cell #atlases a #Cancer cell-cell interactions from variations across individuals Most UC-risk genes are cell type specificVariation – epithelial cell signature – organize US GWAS into cell type spec
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#IESYMPOSIUM @pharma_BI @AVIVA1950 Diane Mathis @HMS Age-dependent Treg and mSC changes – Linear with increase in age Sex-dependent Treg and mSC changes – Female Treg loss in cases of Obesity leading to fibrosis Treg keep IL-33-Producing mSCs under rein Lean tissue/Obese tissue
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#IESYMPOSIUM @pharma_BI @AVIVA1950 Martin LaFleur @HMS Loss of Ptpn2 enhances CD8+ T cell responses to LCMV and Tumors PTpn2 deletion in the immune system enhanced tumor immunity CHIME enables in vivo screening
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#IESYMPOSIUM @pharma_BI @AVIVA1950 Alex Shalek @MIT @kochinstitute Identifying and rationally modulating cellular drivers of enhanced immunity T Cells, Clusters Expression of Peak and Memory Immunotherapy- Identifying Dendritic cells enhanced in HIV-1 Elite Controllers
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Onward: our own Michael Birnbaum, who assures us that if you feel like you’re an immunoengineer, then you ARE one! @kochinstitute

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#IESYMPOSIUM @pharma_BI @AVIVA1950 Glenn Dranoff @Novartis Adenosine level in blood or tissue very difficult to measure in blood even more than in tissue – NIR178 + PDR 001 Monotherapy (NIR178) combine with PD receptor blockage (PDR) show benefit A alone vs A+B in Clinical trial
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#IESYMPOSIUM @pharma_BI @AVIVA1950 Glenn Dranoff @Novartis PD-L1 blockade elicits responses in some patients: soft part sarcoma LAG-3 combined with PD-1 – human peripheral blood tumor TIM-3 key regulator of T cell and Myeloid cell function: correlates in the TCGA DB myeloid
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#IESYMPOSIUM @pharma_BI @AVIVA1950 Glenn Dranoff @Novartis Institute for Biomedical Research #Mechnism of #protective #tumor #immunity Neurologic toxicities of CART t IL-6 activation AML – complete response – weekly dose of XmAb CD123X CD3 bispecific antibody anti tumor effect
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#IESYMPOSIUM @pharma_BI @AVIVA1950 @michaelbirnbaum @MIT @kochinstitute #repertoire of protective #tumor #immunity HLA-DR4 effects outside of “peptide anchor” residues Class I MHC – HLA-E down regulate T and NK cells Receptor Binding: Positional preferences noted for NKG2A
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#IESYMPOSIUM @pharma_BI @AVIVA1950 Yvonne Chen @UCLA Activation of t Cell use CAR t Engineer CAR-T to respond to soluble form of antigens: CD19 CAR Responds to soluble CD19 GFP MCAR responds to Dimeric GFP “Tumor microenvironment is a scary place”
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#IESYMPOSIUM @pharma_BI @AVIVA1950 Yvonne Chen @UCLA Do we need a ligand to be a dimers? Co-expressed second-generation TGF-beta signaling
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#IESYMPOSIUM @pharma_BI @AVIVA1950 Yvonne Chen @UCLA “Engineering smarter and stronger T cells for cancer immunotherapy” OR-Gate cause no relapse – Probing limits of modularity in CAR Design Bispecific CARs are superior to DualCAR: One vs DualCAR (some remained single CAR)
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timisstuck‏ @timisstuck Jan 28

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Ending the 1st session is Cathy Wu of @DanaFarber detailing some amazing work on vaccination strategies for melanoma and glioblastoma patients. They use long peptides engineered from tumor sequencing data. #iesymposium

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timisstuck‏ @timisstuck Jan 28

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Some fancy imaging: Duggan gives a nice demo of how dSTORM imaging works using a micropatterend image of Kennedy Institute for Rheumatology! yay! #iesymposium

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Joseph Palmeri‏ @josephrpalmeri Jan 28

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Lots of interesting talks in the second session of the #iesymposium – effects of lymphoangiogenesis on anti-tumor immune responses, nanoparticle based strategies to improve bNAbs titers/affinity for HIV therapy, and IAPi cancer immunotherapy

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Joseph Palmeri‏ @josephrpalmeri 15 hours ago

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Looking forward to another day of the #iesymposium. One more highlight from yesterday – @nm0min from our own lab showcased her work developing cytokine fusions that bind to collagen, boosting efficacy while drastically reducing toxicities

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Intellia Therapeutics‏ @intelliatweets Jan 28

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Members of our cell therapy team were down the street today at neighboring @MIT for the #iesymposium presented by @kochinstitute. #CRISPR #genomeediting

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John Doench‏ @JohnDoench Jan 28

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Replying to @AEDeconinck @kochinstitute

He could have fooled me that he is, in fact, an immunologist!

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Mike Feigin‏ @mikefeigin Jan 22

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I absolutely LOVE this essay. “Why geneticists stole cancer research even though cancer is primarily a signaling disease”

https://twitter.com/i/cards/tfw/v1/1087802072144273408?cardname=summary&autoplay_disabled=true&forward=true&earned=true&edge=true&lang=en&card_height=130&scribe_context=%7B%22client%22%3A%22web%22%2C%22page%22%3A%22me%22%2C%22section%22%3A%22profile%22%2C%22component%22%3A%22tweet%22%7D&bearer_token=AAAAAAAAAAAAAAAAAAAAAPYXBAAAAAAACLXUNDekMxqa8h%252F40K4moUkGsoc%253DTYfbDKbT3jJPCEVnMYqilB28NHfOPqkca3qaAxGfsyKCs0wRbw#xdm_e=https%3A%2F%2Ftwitter.com&xdm_c=default1249&xdm_p=1

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Come and say Hi! ACIR will be back tomorrow at the Immune Engineering Symposium at MIT. Learn more at http://ow.ly/gk9430ns0QX . #iesymposium @kochinstitute. And stay tuned to read our summary of the talks on Feb 6. #subscribe #newsletter #IO #free

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#IESYMPOSIUM @pharma_BI @AVIVA1950 Facundo Batista @MGH #Vaccine ##evaluation in #humanized #mousemodels BG18 Germline Heavy CHain (BG18-gH) High-mannose patch – mice exhibit normal B cell development B cells from naive human germline BG18-gH bind to GT2 immunogen
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#IESYMPOSIUM @pharma_BI @AVIVA1950 Preeti Sharma, U Illinois T cell receptor and CAR-T engineering TCR engineering for Targeting glycosylated cancer antigens Nornal glycosylation vs Aberrant Engineering 237-CARs libraries with conjugated (Tn-OTS8) against Tn-antigend In vitro
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#IESYMPOSIUM @pharma_BI @AVIVA1950 Bryan Bryson @MIT Loss of polarization potential: scRNAseq reveals transcriptional differences Thioredoxin facilitates immune response to Mtb is a marker of an inflammatory macrophage state functional spectrum of human microphages
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#IESYMPOSIUM @pharma_BI @AVIVA1950 Bryan Bryson @MIT macrophage axis in Mycobacterium tuberculosis Building “libraries” – surface marker analysis of Microphages Polarized macrophages are functionally different quant and qual differences History of GM-CSF suppresses IL-10
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#IESYMPOSIUM @pharma_BI @AVIVA1950 Jamie Spangler John Hopkins University “Reprogramming anti-cancer immunity RESPONSE through molecular engineering” De novo IL-2 potetiator in therapeutic superior to the natural cytokine by molecular engineering mimicking other cytokines
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#IESYMPOSIUM @pharma_BI @AVIVA1950 Jamie Spangler @JHU JES6-1 Immunocytokine – inhibiting melanoma Engineering a Treg cell-biased immunocytokine double mutant immunocytokine shows enhanced IL-2Ralpha exchange Affinity De Novo design of a hyper-stable, effector biased IL-2
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#Cardiovascular #Diseases, Volume Six: #Interventional #Cardiology for #disease #diagnosis and #Cardiac #Surgery for #Condition #Treatment. On com since 12/24/2018 https://lnkd.in/e_CTb4R @Pharma_BI @AVIVA1950

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#Cardiovascular #Diseases, Volume Five: #PharmacologicalAgents in #Treatment of Cardiovascular Diseases. On com since 12/23/2018 https://lnkd.in/e3r87cQ @Pharma_BI @AVIVA1950

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#Cardiovascular #Diseases, Volume Four: #Regenerative and #Translational #medicine : The #Therapeutics #Promise for Cardiovascular Diseases. On com since 12/26/2015 https://lnkd.in/dwqM3K3 @Pharma_BI @AVIVA1950

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#Cardiovascular #Diseases, Volume Three: #Etiologies of #Cardiovascular Diseases: #Epigenetics, #Genetics and #Genomics. On com since 11/29/2015 https://lnkd.in/ecp5mrA @Pharma_BI @AVIVA1950

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#Cardiovascular #Diseases, Volume Two: Cardiovascular #Original #Research: Cases in #Methodology Design for #Content Co-Curation. On com since 11/30/2015 https://lnkd.in/ekbuNZ3 @Pharma_BI @AVIVA1950

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#Cardiovascular #Diseases, Volume One: #Perspectives on #Nitric #Oxide in #Disease #Mechanisms. On com since 6/21/2013 https://lnkd.in/8DANfq @pharma_BI @AVIVA1950

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#IESYMPOSIUM @pharma_BI @AVIVA1950 eProceeding LIVE Day One @KochInstitute @MIT 2019 #Immune #Engineering #Symposium, January 28, 2019, Kresge Auditorium, MIT https://pharmaceuticalintelligence.com/2019/01/28/live-day-one-koch-institute-2019-immune-engineering-symposium-january-28-2019-kresge-auditorium-mit/ … via @Pharma_BI

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#IESYMPOSIUM @pharma_BI @AVIVA1950 Michael Dustin @UniofOxford ESCRT pathway associated with synaptic ectosomes Locatization, Microscopy Cytotoxic T cell granules CTLs release extracellular vescicles similar to T Helper with perforin and granzyme – CTL vesicles kill targets

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#IESYMPOSIUM @pharma_BI @AVIVA1950 Michael Dustin @Oxford Delivery of T cell Effector function through extracellular vesicles Synaptic ectosome biogenisis Model: T cells: DOpamine cascade in germinal cell delivered to synaptic cleft – Effector CD40 – Transfer is cooperative
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#IESYMPOSIUM @pharma_BI @AVIVA1950 Michael Dustin @Oxford Delivery of T cell Effector function through extracellular vesicles Laterally mobile ligands track receptor interaction ICAM-1 Signaling of synapse – Sustain signaling by transient in microclusters TCR related Invadipodia
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#IESYMPOSIUM @pharma_BI @AVIVA1950 Mikael Pittet @MGH Myeloid Cells in Cancer Indirect mechanism AFTER a-PD-1 Treatment IFN-gamma Sensing Fosters IL-12 & therapeutic Responses aPD-1-Mediated Activation of Tumor Immunity – Direct activation and the ‘Licensing’ Model

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#IESYMPOSIUM @pharma_BI @AVIVA1950 Stefani Spranger @MIT KI Response to checkpoint blockade Non-T cell-inflamed – is LACK OF T CELL INFILTRATION Tumor CD103 dendritic cells – Tumor-residing Batf3-drivenCD103 Tumor-intrinsic Beta-catenin mediates lack of T cell infiltration

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#IESYMPOSIUM @pharma_BI @AVIVA1950 Max Krummel @UCSF Gene expression association between two genes: #NK and #cDC1 numbers are tightly linked to response to checkpoint blockage IMMUNE “ACCOMODATION” ARCHYTYPES: MYELOID TUNING OF ARCHITYPES Myeloid function and composition
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#IESYMPOSIUM @pharma_BI @AVIVA1950 Noor Momin, MIT Lumican-cytokines improve control of distant lesions – Lumican-fusion potentiates systemic anti-tumor immunity

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#IESYMPOSIUM @pharma_BI @AVIVA1950 Noor Momin, MIT Lumican fusion to IL-2 improves treatment efficacy reduce toxicity – Anti-TAA mAb – TA99 vs IL-2 Best efficacy and least toxicity in Lumican-MSA-IL-2 vs MSA-IL2 Lumican synergy with CAR-T

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April Pawluk‏ @AprilPawluk Jan 27

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excited to attend the @kochinstitute @MIT immune engineering symposium #iesymposium this week! find me there to chat about @CellCellPress and whether your paper could be a good fit for us!

Koch Institute at MITVerified account @kochinstitute

Join leading immunology researchers at our Immune Engineering Symposium on Jan. 28 & 29. Register now: http://bit.ly/2AOUWH6 #iesymposium

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Dr. Jennifer Gori‏ @gori_jennifer Jan 28

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Bob Schreiber and Tyler Jacks kicked off the #iesymposium with 2 great talks on the role of Class I and Class II neo-Ag in tumor immunogenicity and how the tumor microenvironment alters T cell responsiveness to tumors in vivo

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Joseph Palmeri‏ @josephrpalmeri Jan 28

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Scott Wilson from @UChicago gave a fantastic talk on glycopolymer conjugation to antigens to improve trafficking to HAPCs and enhanced tolerization in autoimmunity models. Excited to learn more about his work at his @MITChemE faculty talk! #iesymposium

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Aviva Lev-Ari‏ @AVIVA1950 Jan 28

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AMAZING Symposinm @AVIVA1950 @Pharma_BI

Erika Siren @SirenErika

Spending the (literal) first day of my fellowship at the @kochinstitute #iesymposium! @DanaFarber Cathy Wu talking about the use of neoantigen targeting cancer vaccines for the treatment of ‘cold’ glioblastoma tumors in pts

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Ajay Vishwakarma‏ @VishwakarmaAj Jan 28

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Immune Engineering Symposium at MIT is underway! #iesymposium @kochinstitute

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ACIR.org‏ @ACIR_org Jan 25

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ACIR is excited to be covering the Immune Engineering Symposium at MIT on January 28-29. Learn more at http://ow.ly/gk9430ns0QX . #iesymposium @kochinstitute

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Aviva Lev-Ari‏ @AVIVA1950 Jan 28

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Tyler Jacks talk was outstanding, Needs be delivered A@TED TALKs, needs become contents in the curriculum of Cell Biology graduate seminar as an Online class. BRAVO @pharma_BI @AVIVA1950

Anne E Deconinck @AEDeconinck

My boss, @kochinstitute director Tyler Jacks, presenting beautiful, unpublished work at our 3rd #iesymposium.

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timisstuck‏ @timisstuck Jan 28

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Here we go!! Today and tomorrow the tippity top immunologists converge at @MIT @kochinstitute #iesymposium

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Joseph Palmeri‏ @josephrpalmeri Jan 28

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Exciting start to this year’s Immune Engineering Symposium put on by @kochinstitute at @MIT. A few highlights from the first section… #iesymposium

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Aviva Lev-Ari‏ @AVIVA1950 Jan 28

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#IESYMPOSIUM @pharma_BI @AVIVA1950 Stephanie Dougan (Dana-Farber Cancer Institute) Dept. Virology IAPi outperforms checkpoint blockade in T cell cold tumors reduction of tumor burden gencitabine cross-presenting DCs and CD8 T cells – T cell low 6694c2

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Aviva Lev-Ari‏ @AVIVA1950 Jan 28

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#IESYMPOSIUM @pharma_BI @AVIVA1950 Darrell Irvine (MIT, Koch Institute; HHMI) Engineering follicle delivery through synthetic glycans: eOD-60mer nanoparticles vs Ferritin-trimer 8-mer (density dependent)
Aviva Lev-Ari‏ @AVIVA1950 Jan 28

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#IESYMPOSIUM @pharma_BI @AVIVA1950 Darrell Irvine (MIT, Koch Institute; HHMI) GC targeting is dependent on complement component CIQ – activation: Mannose-binding lectins recognize eOD-60mer but not eOD monomer or trimers

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#IESYMPOSIUM @pharma_BI @AVIVA1950 Melody Swartz (University of Chicago) Lymphangiogenesis attractive to Native T cells, in VEGF-C tumors T cell homing inhibitors vs block T cell egress inhibitors – Immunotherapy induces T cell killing
Aviva Lev-Ari‏ @AVIVA1950 Jan 28

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Paradigm shift #antigens vs #neoantigens #IESYMPOSIUM @pharma_BI @AVIVA1950

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#IESYMPOSIUM @pharma_BI @AVIVA1950 Cathy Wu @MGH breakthrough for Brain Tumor #vaccine based neoantigen-specific T cell at intracranial site Single cells brain tissue vs single cells from neoantigen specific T cells – intratumoral neoantigen-specific T cells: mutARGAP35-spacific

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#IESYMPOSIUM @pharma_BI @AVIVA1950 Cathy Wu (Massachusetts General Hospital) – CoFounder of NEON Enduring complete radiographic responses after #Neovax + alpha-PD-1 treatment (anti-PD-1) NeoVax vs IVAC Mutanome for melanoma and Glioblastoma clinical trials

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Aviva Lev-Ari‏ @AVIVA1950 Jan 28

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#IESYMPOSIUM @pharma_BI @AVIVA1950 @ScottWilson, U of Chicago IV INJECTION: OVAALBUMIN OVA-P(GALINAC), P(GLCNAC), SUPRESS T CELL RESPONSE #Glycoconjucates Abate T cells response – Reduced cytokine production & increased #T-regs
Aviva Lev-Ari‏ @AVIVA1950 Jan 28

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#IESYMPOSIUM @pharma_BI @AVIVA1950 @TylerJacks @MIT Interrogating markers of T cell dysfunction – chance biology of cells by CRISPR – EGR2 at 2 weeks dysfuntioning is reduced presence of EDR2 mutant class plays role in cell metabolism cell becomes functional regulator CD8 T cell
Aviva Lev-Ari‏ @AVIVA1950 Jan 28

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#IESYMPOSIUM @pharma_BI @AVIVA1950 Bob Schreiber (Wash University of St. Louis) Optimal CD8+ T cells mediated #immuneresponses to T3 #sarcomas require CD4+ T #cell help

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LIVE Day Two – Koch Institute 2019 Immune Engineering Symposium, January 29, 2019, Kresge Auditorium, MIT

Posted in Adaptive Immune Response to Biomaterials and Tissue Repair, Antibody Responses Predict Antigen Exposure, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer-Immune Interactions, Conference Coverage with Social Media, Cytokine Receptor Structure, Efficacy of Anti-Tumor T Cells, Engineering Better T Cells, Human Antibody Response, Human Circulating Antibody Repertoire, Human Naive B Cell Repertoire, Immune Engineering, Immune Modulatory, Immuno-Oncology & Genomics, Immunodiagnostics, Immunology, Immunotherapy, MHC Repertoires for Antigen Prediction, Modulating Macrophages in Cancer Immunotherapy, NK Cell-Based Cancer Immunotherapy, Protection Against Autoimmune Disease, Synergistic Innate and Adaptive Immunotherapy, Synthetic Immunology: Hacking Immune Cells on January 29, 2019| Leave a Comment »

LIVE Day Two – Koch Institute 2019 Immune Engineering Symposium, January 29, 2019, Kresge Auditorium, MIT

Reporter: Aviva Lev-Ari, PhD, RN

Real Time Press Coverage: Aviva Lev-Ari, PhD, RN

Confirmation Number: PVNYDMS4FND
Pamela Difraia pdifraia@mit.edu

#IESYMPOSIUM @pharma_BI @AVIVA1950

MISSION The mission of the Koch Institute (KI) is to apply the tools of science and technology to improve the way cancer is detected, monitored, treated and prevented.

APPROACH We bring together scientists and engineers – in collaboration with clinicians and industry partners – to solve the most intractable problems in cancer. Leveraging MIT’s strengths in technology, the life sciences and interdisciplinary research, the KI is pursuing scientific excellence while also directly promoting innovative ways to diagnose, monitor, and treat cancer through advanced technology.

HISTORY The Koch Institute facility was made possible through a $100 million gift from MIT alumnus David H. Koch. Our new building opened in March 2011, coinciding with MIT’s 150th anniversary. Our community has grown out of the MIT Center for Cancer Research (CCR), which was founded in 1974 by Nobel Laureate and MIT Professor Salvador Luria, and is one of seven National Cancer Institute-designated basic (non-clinical) research centers in the U.S.

https://ki.mit.edu/files/ki/cfile/news/presskit/KI_Fact_Sheet_-_February_2018.pdf

January 28-29, 2019
Kresge Auditorium, MIT

Biological, chemical, and materials engineers are engaged at the forefront of immunology research. At their disposal is an analytical toolkit honed to solve problems in the petrochemical and materials industries, which share the presence of complex reaction networks, and convective and diffusive molecular transport. Powerful synthetic capabilities have also been crafted: binding proteins can be engineered with effectively arbitrary specificity and affinity, and multifunctional nanoparticles and gels have been designed to interact in highly specific fashions with cells and tissues. Fearless pursuit of knowledge and solutions across disciplinary boundaries characterizes this nascent discipline of immune engineering, synergizing with immunologists and clinicians to put immunotherapy into practice.

The 2019 symposium will include two poster sessions and four abstract-selected talks. Abstracts should be uploaded on the registration page. Abstract submission deadline is November 15, 2018. Registration closes December 14.

Featuring on Day 2, 1/29, 2019:

Session IV

Moderator: Michael Birnbaum, Koch Institute, MIT

Jamie Spangler (John Hopkins University)

“Reprogramming anti-cancer immunity through molecular engineering”

Reprogramming anti-cancer immunity response through molecular engineering”
Cytokines induce receptor dimerization
Clinical Use of cytokines: Pleiotropy, expression and stability isssues
poor pharmacological properties
cytokine therapy: New de novo protein using computational methods
IL-2 signals through a dimeric nad a trimeric receptor complex
IL-2 pleiotropy hinders its therapeutic efficacy
IL-2 activate immunosuppression
potentiation of cytokine activity by anti-IL-2 antibody selectivity
Cytokine binding – Antibodies compete with IL-2 receptor subunits
IL-2Ralpha, IL-2 Rbeta: S4B6 mimickry of alpha allosterically enhances beta
stimulates both Effectors and T-regs
JES6-1 immunocomplex selectively stimulates IL-2Ralpha cells
Engineering translational single-chain cytokine/antibody fusion
Engineering an EFFECTOR cell-based immunocytokine (602)
JES6-1 Immunocytokine – inhibiting melanoma
Engineering a Treg cell-biased immunocytokine
double mutant immunocytokine shows enhanced IL-2Ralpha exchange
Affinity – molecular eng De Novo design of a hyper-stable, effector biased IL-2
De novo IL-2 poteniator in therapeutic superior to the natural cytokine by molecular engineering

Bryan Bryson (MIT, Department of Biological Engineering)

“Exploiting the macrophage axis in Mycobacterium tuberculosis (Mtb) infection”

TB – who develop Active and why?
Immunological life cycle of Mtb
Global disease Mtb infection outcome varies within individual host
lesion are found by single bacteria
What are the cellular players in immune success
MACROPHAGES – molecular signals enhancing Mtb control of macrophages
modeling the host- macrophages are plastic and polarize
Building “libraries” – surface marker analysis of Microphages
Polarized macrophages are functionally different
quant and qual differences
History of GM-CSF suppresses IL-10
Loss of polarization potential: scRNAseq reveals transcriptional differences Thioredoxin facilitates immune response to Mtb is a marker of an inflammatory macrophage state
functional spectrum of human microphages

Facundo Batista (Ragon Institute (HIV Research) @MGH, MIT and Harvard)

“Vaccine evaluation in rapidly produced custom humanized mouse models”

Effective B cell activation requires 2 signals Antigen and binding to T cell
VDJ UCA (Unmutated common Ancestor)
B Cell Receptor (BCR) co-receptors and cytoskeleton
44% in Women age 24-44
Prototype HIV broadly neutralizing Antibodies (bnAb) do not bind to Env protein – Immunogen design and validation
Target Identification –>> Immunogen Design –>>> Immunogen Validation
Human Ig Knock-ins [Light variable 5′ chain length vs 7′ length] decisive to inform immunogenicity – One-Step CRISPR approach does not require ES cell work
Proof of principle with BG18 Germline Heavy Chain (BG18-gH) High-mannose patch – mice exhibit normal B cell development
B cells from naive human germline BG18-gH bind to GT2 immunogen
GT2-nanoparticle 9NP) induces robust BG18-gH-500 cells: CD45.2 GL7 IgD
Interrogate immune response for HIV, Malaria, Zika, Flu

Session V

Moderator: Dane Wittrup, Koch Institute, MIT

Yvonne Chen (University of California, Los Angeles)

“Engineering smarter and stronger T cells for cancer immunotherapy”

Adoptive T-Cell Therapy
Tx for Leukemia – Tumor Antigen escape fro CAR T-cell therapy, CD19/CD20 OR-Gate CARs for prevention of antigen escape – 15 month of development
reduce probability of antigen escape due to two antigen CD19/CD20: Probing limits of modularity in CAR design
In vivo model: 75% wild type & 25% CD19 – relapse occur in the long term, early vs late vs no relapse: Tx with CAR t had no relapse
OR-Gate cause no relapse – Probing limits of modularity in CAR Design
Bispecific CARs are superior to DualCAR: One vs DualCAR (some remained single CAR)
Bispecific CARs exhibit superior antigen-stimulation capacity – OR-Gate CAR Outperforms Single-Input CARs
Lymphoma and Leukemia are 10% of all Cancers
TGF-gamma Rewiring T Cell Response
Activation of t Cell use CAR t
Engineer CAR-T to respond to soluble form of antigens: CD19 CAR Responds to soluble CD19
GFP MCAR responds to Dimeric GFP
“Tumor microenvironment is a scary place”

Michael Birnbaum, MIT, Koch Institute

“A repertoire of protective tumor immunity”

Decoding T and NK cell recognition – understanding immune recognition and signaling function for reprogramming the Immune system – Neoantigen vaccine pipeline
Personal neoantigen vax improve immunotherapy
CLASS I and CLASS II epitomes: MHC prediction performance – more accurate for CLASS I HLA polymorphisms
Immune Epitope DB and Analysis Resources 448,630 Peptide Epitomes
B cell assay: 413,000
T cell assays: 313,000
peptide sequence relationships – naturally occurring antigen predictions
Cleavable pMHC yeast display to determine peptide loading
HLA-DR4 libraries enrich a large collection of peptides: 96000 1/5 of entire peptide DB: Enriched motif, prediction algorithms
Algorithmic false negatives vs peptide concentration(nM)
HLA-DR4 effects outside of “peptide anchor” residues
Class I MHC – HLA-E down regulate T and NK cells
Receptor Binding: Positional preferences noted for NKG2A
Training data vs Algorithmic approach
Globally oriented –
TCR sequencing – TCR pairings – Multicell-per-well sequencing
MAD-HYPE algorithm

Glenn Dranoff, Novartis Institute for Biomedical Research

“Mechnism of protective tumor immunity”

Immune checkpoint blockade elicit 10 years survival in melanoma
PD-1 blockage esophageal carcinoma effective showing survival
renal cells, bladder
20% benefit from Immuno therapy – CTLA-4 toxicity is high small % patient benefit
PD-1/PD-L1 anti CLTA-4 mAbs
solid tumors challenging
Requirement for effective IO – Tumor receptivity to immune infiltration
modulation
Novartis IO in the clinic: multiple tumor immune escape – complexity
Approach: focus trials aimed to learn immune response complementation groups manipulate into response
work with Engineering for delivery nimble to generate new data
Translational research in the clinic
CAR T cells
B cell malignancies are ideal targets for CAR T cells
Relapsed/Refractory – pediatric ALL refractory advanced to no relapse – complete response 80% – 6 years response
Antigen loss CD19 – targeting with combinatorial approach to avoid relapse
Large B cell lymphoma
Neurologic toxicities of CART t IL-6 activation
AML – complete response – weekly dose of XmAb CD123X CD3 bispecific antibody – protein engineering – anti tumor effect in refractory Leukemia
anaplastic thyroid carcinoma
PD-L1 blockade elicits responses in some patients: soft part sarcoma
LAG-3 combined with PD-1 – human peripheral blood tumor
TIM-3 key regulator of T cell and Myeloid cell function: correlates in the TCGA DB with myeloid
Adenosine level in blood or tissue very difficult to measure in blood even more than in tissue – NIR178 + PDR 001 Mono-therapy (NIR178) combine with PD receptor blockage (PDR) – shows benefit
A alone vs A+B in Clinical trial

Session VI

Moderator: Stefani Spranger, Koch Institute, MIT

Tim Springer, Boston Children’s Hospital, HMS

The Milieu Model for TGF-Betta Activation”

Protein Science – Genomics with Protein
Antibody Initiative – new type of antibodies not a monoclonal antibody – a different type
Pro TGF-beta
TGF-beta – not a typical cytokine it is a prodamine for Mature growth factor — 33 genes mono and heterogeneous dimers
Latent TGF-Beta1 crystal structure: prodomaine shields the Growth Factor
Mechanism od activation of pro-TGF-beta – integrin alphaVBeta 6: pro-beta1:2
Simulation in vivo: actin cytoskeleton cytoplasmic domain
LIFE CYCLE OF PROTGF-BETA
LRRC33 – GARP class relative
microglia and macrophage – link TGF-beta phenotype knock outs
TGF compartments of microglia separated myelination loss
Inhibition of TGF-beta enhances immune checkpoint
Loss of LRRC33-dependent TGF-beta signaling would counteract immune suppression in tumor and in slow tumor growth
lung metastasis of B16 in melanoma
immuno-histo-chemistry: LRRC33 tumor-associated myeloid cell lack cell surface proTGF-beta1
blocking antibodies LRRC33 mitigate toxicity on PD-L1 treatment

Alex Shalek, MIT, Department of Chemistry, Koch Institute

“Identifying and rationally modulating cellular drivers of enhanced immunity”

Balance in the Immune system
Profiling Granulomas using Seq-Well 2.0
lung tissue in South Africa of TB patients
Granulomas, linking cell type abundance with burden
Exploring T cells Phenotypes
Cytotoxic & Effector ST@+ Regulatory
Vaccine against TB – 19% effective, only 0 IV BCG vaccination can elicit sterilizing Immunity
Profiling cellular response to vaccination
T cell gene modules across vaccine routes
T Cells, Clusters
Expression of Peak and Memory
Immunotherapy- Identifying Dendritic cells enhanced in HIV-1 Elite Controllers
moving from Observing to Engineering
Cellular signature: NK-kB Signaling
Identifying and testing Cellular Correlates of TB Protection
Beyond Biology: Translation research: Data sets: dosen

Session VII

Moderator: Stefani Spranger, Koch Institute, MIT

Diane Mathis, Harvard Medical School

“Tissue T-regs”

T reg populations in Lymphoid Non–lymphoid Tissues
2009 – Treg tissue homeostasis status – sensitivity to insulin, 5-15% CD4+ T compartment
transcriptome
expanded repertoires TCRs
viceral adipose tissue (VAT) – Insulin
Dependencies: Taget IL-33 its I/1r/1 – encoded Receptor ST2
VAT up-regulate I/1r/1:ST2 Signaling
IL-33 – CD45 negative CD31 negative
mSC Production of IL-33 is Important to Treg
The mesenchyme develops into the tissues of the lymphatic and circulatory systems, as well as the musculoskeletal system. This latter system is characterized as connective tissues throughout the body, such as bone, muscle and cartilage. A malignant cancer of mesenchymal cells is a type of sarcoma.
mesenchymal Stromal Cells – mSC – some not all, VAT mSCs express IL-33
development of a mAb Panel for sorting the mSC Subtypes
Deeper transcriptome for Phenotyping of VAT mSCs
physiologic & pathologic perturbation

Age-dependent Treg and mSC changes – Linear with increase in age
Sex-dependent Treg and mSC changes – Female

Treg loss in cases of Obesity leading to fibrosis
Treg keep IL-33-Producing mSCs under rein
Lean tissue vs Obese tissue
Aged mice show poor skeletal muscle repair – it is reverses by IL-33 Injection
Immuno-response: target tissues systemic T reg
Treg and mSC

Aviv Regev, Broad Institute; Koch Institute

“Cell atlases as roadmaps to understand Cancer”

Colon disease UC – genetic underlining risk, – A single cell atlas of healthy and UC colonic mucosa inflammed and non-inflammed: Epithelial, stromal, Immune – fibroblast not observed in UC colon IAFs; IL13RA2 + IL11
Anti TNF responders – epithelial cells
Anti TNF non-responders – inflammatory monocytes fibroblasts
RESISTANCE to anti-cancer therapy: OSM (Inflammatory monocytes-OSMR (IAF)
cell-cell interactions from variations across individuals
Most UC-risk genes are cell type specific
Variation within a cell type helps predict GWAS gene functions – epithelial cell signature – organize US GWAS into cell type specific – genes in associated regions: UC and IBD

Melanoma
malignant cells with resistance in cold niches in situ
cells express the resistance program pre-treatment: resistance UP – cold
Predict checkpoint immunotherapy outcomes
CDK4/6 – computational search predict as program regulators: abemaciclib in cell lines

Poster Presenters

Preeti Sharma, University of Illinois

T cell receptor and CAR-T engineering – T cell therapy

TCR Complex: Vbeta Cbeta P2A Valpha Calpha
CAR-T Aga2 HA scTCR/scFv c-myc
Directed elovution to isolate optimal TCR or CAR
Eng TCR and CARt cell therapy
Use of TCRs against pep/MHC allows targeting a n array of cancer antigens
TCRs are isolated from T cell clones
Conventional TCR identification method vs In Vitro TCR Eng directed evolution
T1 and RD1 TCRs drive activity against MART-1 in CD4+ T cells
CD8+
TCR engineering for Targeting glycosylated cancer antigens
Normal glycosylation vs Aberrant glycosylation
Engineering 237-CARs libraries with conjugated (Tn-OTS8) against multiple human Tn-antigend
In vitro engineering: broaden specificity to multiple peptide backbone
CAR engineering collaborations with U Chicago, U Wash, UPenn, Copenhagen, Germany

Martin LaFleur, HMS

CRISPR- Cas9 Bone marrow stem cells for Cancer Immunotherapy

CHIME: CHimeric IMmune Editing system
sgRNA-Vex
CHIME can be used to KO genes in multiple immune lineages
identify T cell intrinsic effects in the LCMV model Spleen-depleted, Spleen enhanced
Loss of Ptpn2 enhances CD8+ T cell responses to LCMV and Tumors
Ptpn2 deletion in the immune system enhanced tumor immunity
CHIME enables in vivo screening

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Older Posts »

1.1 REPORT DESCRIPTION	17
1.2 TOPICS COVERED	19
1.3 KEY MARKET SEGMENTS	20
1.4 KEY BENEFITS	21
1.5 RESEARCH METHODOLOGY	21
1.6 TARGET AUDIENCE	22
1.7 COMPANIES MENTIONED	23

3.1 MARKET DEFINITION AND SCOPE	30
3.2 KEY FINDINGS	31
3.3 TOP INVESTMENT POCKETS	32
3.4 TOP WINNING STRATEGIES	33
3.4.1.Top winning strategies, by year, 2017-2019*	34
*3.4.2.Top winning strategies, by development, 2017-2019(%)**	34
3.4.3.Top winning strategies, by company, 2017-2019*	35
3.5 TOP PLAYER POSITIONING, BY PIPELINE VOLUME, 2019	38
3.6 PORTERS FIVE FORCES ANALYSIS	39
3.7 COVID19 IMPACT ON CELL AND GENE THERAPY (CGT) INDUSTRY	41
3.8 MARKET DYNAMICS	46
3.8.1 Drivers	46
3.8.1.1 Increase in funding for R&D activities of CAR T-cell therapy	46
3.8.1.2 The rise in the prevalence of cancer	47
3.8.1.3 Increase in awareness regarding CAR T-cell therapy	47

3.8.2 Restrains	48
3.8.2.1 The high cost of CAR T-cell therapy treatment	48
3.8.2.2 Unwanted immune responses and side effects	48
3.8.2.3 Long production time	48
3.8.2.4 Obstacles in treating solid tumors	49
3.8.3 Opportunities	49
3.8.3.1 Untapped potential for emerging markets	49

4.1 OVERVIEW	50
4.2 SIXTY YEARS HISTORY OF CAR T-CELL THERAPY	51
4.3 CAR T-CELL STRUCTURE AND GENERATIONS	53
4.4 CAR T-CELL MANUFACTURING PROCESSES	56
4.5 PRICING AND PAYMENT MODELS FOR CAR T-CELL THERAPIES	59

5.1 OVERVIEW	61
5.1.1 Market size and forecast	62
5.2 AUTOLOGOUS	63
5.2.1 Key market trends	63
5.2.2 Key growth factors and opportunities	64
5.2.3 Market size and forecast	64
5.2.4 Market size and forecast by country	65
5.3 ALLOGENEIC	66
5.3.1 Key market trends	67
5.3.2 Key growth factors and opportunities	68
5.3.3 Market size and forecast	68
5.3.4 Market size and forecast by country	69

6.1 OVERVIEW	70
6.1.1 Market size and forecast	71
6.2 CD19	72
6.2.1 Market size and forecast	73
6.2.2 Market size and forecast by country	74

6.3 CD20		75
6.3.1	Market size and forecast	76
6.3.2	Market size and forecast by country	77
6.4 BCMA		78
6.4.1	Market size and forecast	79
6.4.2	Market size and forecast by country	80
6.5 MSLN		81
6.5.1	Market size and forecast	82
6.5.2	Market size and forecast by country	83
6.6 OTHERS		84
6.6.1	Market size and forecast	85
6.6.2	Market size and forecast by country	86

7.1 OVERVIEW	87
7.1.1 Market size and forecast	88
7.2 ACUTE LYMPHOBLASTIC LEUKEMIA (ALL)	89
7.2.1 Market size and forecast	90
7.2.2 Market size and forecast by country	91
7.3 DIFFUSE LARGE B-CELL LYMPHOMA (DLBCL)	92
7.3.1 Market size and forecast	93
7.3.2 Market size and forecast by country	94
7.4 MULTIPLE MYELOMA (MM)	95
7.4.1 Market size and forecast	96
7.4.2 Market size and forecast by country	97
7.5 ACUTE MYELOID LEUKEMIA (AML)	98
7.5.1 Market size and forecast	99
7.5.2 Market size and forecast by country	100
7.6 OTHERS	101
7.6.1 Market size and forecast	102
7.6.2 Market size and forecast by country	103

8.1 OVERVIEW	104
8.1.1 Market size and forecast	104
8.2 NORTH AMERICA	105
8.2.1 Key market trends	105
8.2.2 Key growth factors and opportunities	105

8.2.3 Market size and forecast, by country		106
8.2.4 Market size and forecast, by approach type		106
8.2.5 Market size and forecast, by antigen type		107
8.2.6	Market size and forecast, by application	107
8.2.6.1	U.S. market size and forecast, by approach type	108
8.2.6.2	U.S. market size and forecast, by antigen type	108
8.2.6.3	U.S. market size and forecast, by application	109
8.2.6.4	Canada market size and forecast, by approach type	110
8.2.6.5	Canada market size and forecast, by antigen type	110
8.2.6.6	Canada market size and forecast, by application	111
8.2.6.7	Mexico market size and forecast, by approach type	112
8.2.6.8	Mexico market size and forecast, by antigen type	112
8.2.6.9	Mexico market size and forecast, by application	113
8.3 EUROPE		114
8.4.1	Key market trends	114
8.4.2	Key growth factors and opportunities	114
8.4.3	Market size and forecast, by country	115
8.4.4	Market size and forecast, by approach type	115
8.4.5	Market size and forecast, by antigen type	116
8.4.6	Market size and forecast, by application	116
8.3.6.1	UK market size and forecast, by approach type	117
8.3.6.2	UK market size and forecast, by antigen type	117
8.3.6.3	UK market size and forecast, by application	118
8.3.6.4	Germany market size and forecast, by approach type	119
8.3.6.5	Germany market size and forecast, by antigen type	119
8.3.6.6	Germany market size and forecast, by application	120
8.3.6.7	France market size and forecast, by approach type	121
8.3.6.8	France market size and forecast, by antigen type	121
8.3.6.9	France market size and forecast, by application	122
8.3.6.10	Spain market size and forecast, by approach type	123
8.3.6.11	Spain market size and forecast, by antigen type	123
8.3.6.12	Spain market size and forecast, by application	124
8.3.6.13	Italy market size and forecast, by approach type	125
8.3.6.14	Italy market size and forecast, by antigen type	125
8.3.6.15	Italy market size and forecast, by application	126
8.3.6.16	Rest of Europe market size and forecast, by approach type	127
8.3.6.17	Rest of Europe market size and forecast, by antigen type	127
8.3.6.18	Rest of Europe market size and forecast, by application	128
8.4 ASIA-PACIFIC		129
8.4.1	Key market trends	129
8.4.2	Key growth factors and opportunities	129
8.4.3	Market size and forecast, by country	130
8.4.4	Market size and forecast, by approach type	130

8.4.5 Market size and forecast, by antigen type		131
8.4.6	Market size and forecast, by application	131
8.4.6.1	China market size and forecast, by approach type	132
8.4.6.2	China market size and forecast, by antigen type	132
8.4.6.3	China market size and forecast, by application	133
8.4.6.4	Japan market size and forecast, by approach type	134
8.4.6.5	Japan market size and forecast by antigen type	134
8.4.6.6	Japan market size and forecast, by application	135
8.4.6.7	India market size and forecast, by approach type	136
8.4.6.8	India market size and forecast, by antigen type	136
8.4.6.9	India market size and forecast, by application	137
8.4.6.10	South Korea market size and forecast, by approach type	138
8.4.6.11	South Korea market size and forecast, by antigen type	138
8.4.6.12	South Korea market size and forecast, by application	139
8.4.6.13	Rest of Asia-Pacific market size and forecast, by approach type	140
8.4.6.14	Rest of Asia-Pacific market size and forecast, by antigen type	140
8.4.6.15	Rest of Asia-Pacific market size and forecast, by application	141
8.5 LAMEA		142
8.5.1	Key market trends	142
8.5.2	Key growth factors and opportunities	142
8.5.3	Market size and forecast, by country	143
8.5.4	Market size and forecast, by approach type	143
8.5.5	Market size and forecast, by antigen type	144
8.5.6	Market size and forecast, by application	144
8.5.6.1	Brazil market size and forecast by approach type	145
8.5.6.2	Brazil market size and forecast, by antigen type	145
8.5.6.3	Brazil market size and forecast, by application	146
8.5.6.4	South Africa market size and forecast, by approach type	147
8.5.6.5	South Africa market size and forecast, by antigen type	147
8.5.6.6	South Africa market size and forecast, by application	148
8.5.6.7	Rest of LAMEA market size and forecast by approach type	149
8.5.6.8	Rest of LAMEA market size and forecast, by antigen type	149
8.5.6.9	Rest of LAMEA market size and forecast, by application	150

9.1 OVERVIEW	151
9.1.1 No. of Clinical Trials from 1997 to 2019	151
9.1.2 Clinical Trials from 1997 to 2019: Based on Approach Type	152
9.1.3 Clinical Trials from 1997 to 2019: Based on Antigen Type	153
9.1.4 Clinical Trials from 1997 to 2019: Based on Application	154
9.1.5 Clinical Trials from 1997 to 2019: Based on Region	155

9.2 EXPECTED APPROVALS	156
9.3 APPROVED PRODUCTS PROFILES	157
9.3.1 KYMRIAH®	157
9.3.2 YESCARTA®	159
9.3.3 TECARTUS™	161

10.1 Abbvie Inc.		162
10.2 Adaptimmune Therapeutics Plc		164
10.3	Allogene Therapeutics, Inc.	166
10.4	Amgen, Inc	168
10.5	Anixa Biosciences, Inc.	170
10.6	Arcellx, Inc.	172
10.7	Atara Biotherapeutics, Inc.	173
10.8	Autolus Therapeutics Plc.	175
10.9	Beam Therapeutics, Inc.	177
10.10	Bellicum Pharmaceuticals, Inc.	179
10.11	BioNtech SE	181
10.12	Bluebird Bio, Inc.	183
10.13	Carsgen Therapeutics, Ltd	185
10.14	Cartesian Therapeutics, Inc.	187
10.15	Cartherics Pty Ltd.	188
10.16	Celgene Corporation	189
10.17	Cellectis SA	191
10.18	Cellular Biomedicine Group, Inc.	193
10.19	Celularity, Inc.	195
10.20	Celyad SA	196
10.21	CRISPR Therapeutics AG	198
10.22	Eureka Therapeutics, Inc.	200
10.23	Fate Therapeutics, Inc.	201
10.24	Fortress Biotech, Inc	203
10.25	Gilead Sciences, Inc.	205
10.26	Gracell Biotechnology Ltd	207
10.27	icell Gene Therapeutics	208
10.28	Johnson & Johnson	209
10.29	Juventas Cell Therapy Ltd.	211
10.30	Kuur Therapeutics	212
10.31	Legend Biotech Corp.	213
10.32	Leucid Bio Ltd.	214
10.33	Minerva Biotechnologies Corp.	215

10.34 Molecular Medicine SPA (Molmed)	216
10.35 Nanjing Bioheng Biotech Co., Ltd.	218
10.36 Noile-Immune Biotech Inc.	219
10.37 Novartis AG	220
10.38 Oxford Biomedica PLC	222
10.39 Persongen Biotherapeutics (Suzhou) Co., Ltd.	224
10.40 Poseida Therapeutics, Inc.	226
10.41 Precigen, Inc.	227
10.42 Precision Biosciences, Inc.	229
10.43 Sorrento Therapeutics, Inc.	231
10.44 Takara Bio Inc.	233
10.45 Takeda Pharmaceutical Company Ltd.	235
10.46 TC Biopharm Ltd.	237
10.47 Tessa Therapeutics Pte Ltd.	238
10.48 Tmunity Therapeutics, Inc.	239
10.49 Unum Therapeutics Inc.	240
10.50 Xyphos Inc.	242
10.51 Ziopharm Oncology, Inc.	243

11.1 STRATEGIC RECOMMENDATIONS	245
11.2 CONCLUSION	247

Funding, Deals & Partnerships: BIOLOGICS & MEDICAL DEVICES; BioMed e-Series; Medicine and Life Sciences Scientific Journal – http://PharmaceuticalIntelligence.com

Archive for the ‘Immune Modulatory’ Category

New studies link cell cycle proteins to immunosurveillance of premalignant cells

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The global CAR T-cell therapy market was valued at $734 million in 2019 and is estimated to reach $4,078 million by 2027, registering a CAGR of 23.91% from 2020 to 2027.

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A Series of Recently Published Papers Report the Development of SARS-CoV2 Neutralizing Antibodies and Passive Immunity toward COVID19

1. Cross-neutralization of SARS-CoV-2 by a human monoclonal SARS-CoV antibody.

2. Potent neutralizing antibodies against SARS-CoV-2 identified by high-throughput single-cell sequencing of convalescent patients’ B cells

3. A human monoclonal antibody blocking SARS-CoV-2 infection

For More Articles on COVID-19 Please see Our Coronavirus Portal on this Open Access Scientific Journal at:

and the following Articles on Immunity at

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Reporter and Curator: Dr. Sudipta Saha, Ph.D.

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Newly Found Functions of B Cell

Other advances that are providing insight include:

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CytoReason is re-defining the Context of the Immune System for Drug Discovery

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Quantifying The Age Of Our Immune System Could Bring Us Some Steps Closer To Precision Medicine

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TWEETS by @pharma_BI and @AVIVA1950 at #IESYMPOSIUM – @kochinstitute 2019 #Immune #Engineering #Symposium, 1/28/2019 – 1/29/2019

eProceedings for Day 1 and Day 2

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LIVE Day Two – Koch Institute 2019 Immune Engineering Symposium, January 29, 2019, Kresge Auditorium, MIT

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January 28-29, 2019 Kresge Auditorium, MIT

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January 28-29, 2019
Kresge Auditorium, MIT