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Land | Storbritannien |
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Sektor | Hälsovård |
Industri | Läkemedel & Handel |
Novel Imfinzi-based regimen significantly improved patient outcomes in resectable non-small cell lung cancer in AEGEAN Phase III trial.
Strength of emerging proprietary antibody drug conjugates technology demonstrated with data across three assets.
First clinical data for CAR-T cell therapy in solid tumours utilising AstraZeneca's innovative research and armouring platform.
AstraZeneca will present new data across its diverse, industry-leading Oncology pipeline and portfolio at the American Association for Cancer Research (AACR) Annual Meeting, 14 to 19 April 2023.
Data from 70 presentations will be featured, including eight oral presentations, a plenary presentation of the AEGEAN Phase III trial of Imfinzi (durvalumab) based regimen in resectable non-small cell lung cancer (NSCLC), and the first disclosures of preclinical data for five novel molecules across the Company's Antibody Drug Conjugate (ADC), Cell Therapy and Epigenetics scientific platforms.
Susan Galbraith, Executive Vice President, Oncology R&D, AstraZeneca, said: "It's exciting to see our strategy to attack cancer from multiple angles come to life at AACR this year through data from our proprietary antibody drug conjugates, next generation cell therapies and epigenetics molecules. Furthermore, results from the AEGEAN trial show the potential of treating lung cancer patients early with Imfinzi before and after surgery which reinforces the importance of diagnosing lung cancer early."
Improving outcomes for patients with resectable lung cancer with Imfinzi
A late-breaking presentation of the AEGEAN Phase III trial results will highlight the potential of a novel Imfinzi-based treatment before and after surgery for patients with resectable early-stage (IIA-IIIB) NSCLC. AEGEAN has met its two primary endpoints, demonstrating improvements in event-free survival (https://www.astrazeneca.com/media-centre/press-releases/2023/imfinzi-improved-efs-in-resectable-lung-cancer.html) and pathologic complete response (https://www.astrazeneca.com/media-centre/press-releases/2022/imfinzi-improved-pcr-in-resectable-lung-cancer.html) with Imfinzi in combination with neoadjuvant chemotherapy before surgery and as adjuvant monotherapy versus neoadjuvant chemotherapy alone followed by surgery.
Delivering the next wave of ADCs with proprietary platform
Two oral presentations will feature the first preclinical and translational results for AZD9592, a bispecific ADC designed to deliver targeted chemotherapy to cancer cells with a topoisomerase inhibitor 1 (TOP1i) warhead using the Company's proprietary linker technology.
AZD9592 binds to two known oncogenic drivers: epidermal growth factor receptor (EGFR) and mesenchymal-epithelial transition factor (cMET). These two drivers are often co-expressed in solid tumours including in NSCLC and head and neck squamous cell carcinoma (HNSCC). This is the Company's first bispecific ADC to enter the clinic and shows a promising efficacy and safety profile in preclinical models, with evidence for DNA damage dependent tumour cell death as the mechanism of action.
In addition, the first preclinical results will be presented for another ADC, AZD5335, a promising therapeutic candidate for the treatment of certain ovarian cancers. This ADC has a folate receptor alpha (FRα) targeting antibody linked to a proprietary TOP1i warhead. A robust anti-tumour response is reported in FRα-expressing preclinical models that are resistant to another FRα ADC with a microtubule inhibitor warhead. In addition, AZD5335 is active in models with either high or low levels of target expression as detected by computational pathology.
Preclinical data for AZD8205, an ADC targeting B7-H4, will also be presented both as monotherapy and in combination with the PARP-1 selective inhibitor, AZD5305. Robust anti-tumour activity is evident in preclinical models across multiple B7-H4 positive tumour types, including ovarian and cholangiocarcinoma tumours, with combination therapy resulting in higher anti-tumour activity than monotherapy.
Building the next generation of cell therapies in solid tumours
In cell therapy, the first clinical data will be presented for C-CAR031, a novel transforming growth factor-beta (TGFβ) armoured Glypican 3 (GPC3) targeting chimeric antigen receptor T cell (CAR-T) therapy that is being investigated for liver cancer. Early results show it is well tolerated with promising anti-tumour activity seen with objective responses in several patients to date.
The CAR-T is based on AZD5851, a novel cell therapy that was designed by AstraZeneca, and is being developed and manufactured by Cellular Bioscience Medicine group (CBMG). AstraZeneca's TGFβ armouring is designed to resist the immuno-suppressive tumour microenvironment and enhance the potential effectiveness of CAR-Ts in solid tumours.
In addition, the first preclinical data will be shared on AZD0754, a novel TGFβ armoured CAR-T targeting STEAP2, a protein commonly overexpressed in prostate cancer. This is the first cell therapy to be designed, manufactured and developed by AstraZeneca. The presentation will show encouraging preclinical safety data and supports future clinical development of this potential first-in-class CAR-T therapy.
First disclosure and preclinical data for an epigenetics molecule targeting PRMT5
Epigenetic therapy is one of AstraZeneca's six core scientific areas of focus. The modality is the latest addition to the Company's diverse portfolio, which is designed to attack cancer from multiple angles and redefine outcomes for patients with high unmet needs.
At AACR, the first preclinical data will be presented for the novel lead epigenetics molecule, AZ-PRMT5i-1, a potent methylthioadenosine phosphorylase (MTAP)-selective PRMT5 inhibitor with anti-tumour activity in MTAP-deleted tumours. Loss of the MTAP gene occurs across approximately 15% of all cancers, which provides an opportunity to use a biomarker selection strategy and also spare healthy tissue. The preclinical results demonstrate MTAP selectivity and promising anti-tumour activity.
Harnessing transformational technologies
Transformational technologies, including circulating tumour DNA (ctDNA), computational pathology, and data science and artificial intelligence (AI), underpin the success of progressing AstraZeneca's pipeline. Several presentations at AACR showcase the Company's efforts to harness the power of these technologies to better understand complex cancer biology, identify and select patients for treatment and increase the probability of success in the clinic.
Key AstraZeneca presentations during AACR 2023
[]
Lead author Abstract title Presentation details
IO
Heymach, JV CT005 - AEGEAN: Abstract #CT005Plenary Harnessing the Immune
A phase 3 trial System in the Clinic 16 April 202314:45 -
of neoadjuvant 15:00 ET
durvalumab +
chemotherapy
followed by
adjuvant
durvalumab in
patients with
resectable NSCLC
Iyer S Immunomodulatory Abstract #CT039Clinical Trials
effects of MinisymposiumNovel Immunotherapy Combination
ceralasertib in Clinical Trials18 April 202315:50 - 16:00 ET
combination with
durvalumab in
NSCLC patients
with progression
on anti-PD-(L)1
treatment
(HUDSON,
NCT03334617)
ADCs
Gymnopoulos, First disclosure Abstract #LB025 / 17PosterLate-Breaking
M of AZD5335, a Research: Experimental and Molecular
TOP1i-ADC Therapeutics 116 April 202313:30 - 17:00 ET
targeting low
and high FRα
-expressing
ovarian cancer
with superior
preclinical
activity vs FRα
-MTI ADC
Comer, F AZD9592: an EGFR Abstract #5736MinisymposiumNew Tricks for
-cMET bispecific Known Targets: Novel Approaches to Inhibit
antibody-drug Oncogenic Signaling 18 April 202315:22 -
conjugate (ADC) 15:37 ET
targeting key
oncogenic
drivers in non
-small-cell lung
cancer (NSCLC)
and beyond
McGrath, L Evaluation of Abstract #5737MinisymposiumNew Tricks for
the relationship Known Targets: Novel Approaches to Inhibit
between target Oncogenic Signaling 18 April 202315:37 -
expression and 15:52 ET
in vivo anti
-tumour efficacy
of AZD9592, an
EGFR/c-MET
targeted
bispecific
antibody drug
conjugate
Cazes, A Preclinical Abstract #2947 / 25PosterTherapeutic
evaluation of a Antibodies 217 April 202313:30 - 17:00 ET
novel B7-H4
-targeted
antibody-drug
conjugate
AZD8205 as a
single agent and
in combination
with novel PARP
inhibitor and
checkpoint
blockade
Meric TROPION Abstract #CT058 / 16PosterPhase II and Phase
-Bernstam, F -PanTumor03: III Clinical Trials in Progress17 April
Phase 2, 20239:00 - 12:30 ET
multicenter
study of
datopotamab
deruxtecan (Dato
-DXd) as
monotherapy and
in combination
with anticancer
agents in
patients (pts)
with
advanced/metastat
ic solid tumours
Bhavsar, D Combination of T Abstract #3999 / 22PosterOncogenes and Tumour
-DXd with the Suppressor Genes as Targets for Therapy 3 18
irreversible pan April 20239:00 - 12:30 ET
-HER TKI
afatinib drives
combination
benefit in HER2
-low gastric and
lung tumours
Wray, R. Improving Abstract #LB143 / 7PosterLate-Breaking
Treatment Research: Population Sciences17 April
Outcomes: A 202313:30 - 17:00 ET
Digital Solution
for Remote
Patient
Monitoring of
Stomatitis for
Patients
receiving Dato
-DXd
Cell Therapy
van Dyk, D Antitumour Abstract #LB085 / 1PosterLate-Breaking
activity of Research: Immunology 117 April 20239:00 -
AZD0754, a 12:30 ET
dnTGFbR2 armored
STEAP2 targeted
CAR-T therapy,
in preclinical
models of
prostate cancer
Zhang, Q First report of Abstract #CT097 / 5PosterFirst-in-Human Phase
preliminary I Clinical Trials 117 April 202313:30 - 17:00
safety, ET
efficacy, and
pharmacokinetics
of C-CAR031
(GPC3-specific
TGFBRIIDN CAR-T)
in patients with
advanced HCC
Epigenetics
Smith, JM Identification Abstract #3088 / 1PosterTargeted Drug Design
of a novel and Development for Cancer Therapy 17 April
series of MTAP 202313:30 - 17:00 ET
-selective PRMT5
inhibitors, and
first disclosure
of AZ-PRMT5i-1
Lynch, J AZ-PRMT5i-1: A Abstract #6272 / 10PosterEpigenetics19 April
potent MTAP 20239:00 - 12:30 ET
-selective PRMT5
inhibitor with
pharmacodynamic
and monotherapy
anti-tumour
activity in MTAP
-deleted tumours
TDR[1]
Zhi Peng A Multicenter Abstract # CT152Phase II Clinical Trials 117
Phase II Study April 2023 13:30 - 17:00 ET
of Savolitinib
in Patients with
MET-Amplified
Gastroesophageal
Junction
Adenocarcinomas
or Gastric
Cancer
ctDNA
Labrousse, P The evolution of Abstract #LB293 / 6PosterLate-Breaking
MRD assays; Research: Clinical Research 319 April
moving beyond 20239:00 - 12:30 ET
the tumour
-informed
bespoke NGS
panel
Russell, H Evaluation of a Abstract #3384 / 27PosterLiquid Biopsies:
tumour informed Circulating Nucleic Acids and Circulating
MRD assay with Tumour Cells 317 April 202313:30 - 17:00 ET
contrived breast
cancer samples
Munugalavadla Utility of ctDNA Abstract #3369 / 12PosterLiquid Biopsies:
V -based targeted Circulating Nucleic Acids and Circulating
methylation MRD Tumour Cells 317 April 202313:30 - 17:00 ET
assay for
hematological
malignancies
Hartmaier, R Baseline and on Abstract #LB294 / 7PosterLate-Breaking
-treatment Research: Clinical Research 319 April
plasma-based 20239:00 - 12:30 ET
genomics as a
predictor of
outcomes in
SAVANNAH:
savolitinib +
osimertinib in
EGFRm MET
overexpressed/amp
lified NSCLC
post-osimertinib
Data Science
& AI
Arango G Translating Abstract #5359 / 8PosterArtificial
state-of-the-art Intelligence and Machine/Deep Learning 118
deep learning April 202313:30 - 17:00 ET
predictions of
IO treatment
efficacy to
clinical
practice
Arango G Enhancing the Abstract #1174MinisymposiumAdvancing Cancer
utilization of Research Through an International Cancer
deep learning to Registry: AACR Project GENIE Use Cases16
predict patient April 202315:36 - 15:51 ET
response in
small
immunotherapy
cohorts using
real world data
Nikolau N Improving Abstract #5395 / 11PosterArtificial
survival Intelligence and Machine/Deep Learning 218
prediction using April 202313:30 - 17:00 ET
flexible late
fusion machine
learning
framework for
multi-omics data
integration
Arango G Improved Abstract #5360 / 9PosterArtificial
identification Intelligence and Machine/Deep Learning 118
of CHIP April 202313:30 - 17:00 ET
mutations from
cell free DNA
without matched
normal samples
using machine
learning
Ellen JG Autoencoder Abstract #5373 / 22PosterArtificial
-based Intelligence and Machine/Deep Learning 118
multimodal April 202313:30 - 17:00 ET
prediction of
survival for non
-small cell lung
cancer
Computational
Pathology
Potdevin, G A first Abstract #3577 / 2PosterPET, MRI, and CT
assessment of Imaging18 April 20239:00 - 12:30 ET
CD8-PET/CT with
89-Zr
-Crefmirlimab as
predictive
biomarker for
response to
standard of care
immunotherapy in
patients with
solid tumours
Brieu, N A unified Abstract #5388 / 4PosterArtificial
computational Intelligence and Machine/Deep Learning 218
pathology method April 202313:30 - 17:00 ET
to quantify HER2
expression from
raw IHC and IF
images in breast
cancer
[1] Tumour Drivers and resistance
Notes
AstraZeneca in oncology
AstraZeneca is leading a revolution in oncology with the ambition to provide cures for cancer in every form, following the science to understand cancer and all its complexities to discover, develop and deliver life-changing medicines to patients.
The Company's focus is on some of the most challenging cancers. It is through persistent innovation that AstraZeneca has built one of the most diverse portfolios and pipelines in the industry, with the potential to catalyse changes in the practice of medicine and transform the patient experience.
AstraZeneca has the vision to redefine cancer care and, one day, eliminate cancer as a cause of death.
AstraZeneca
AstraZeneca (LSE/STO/Nasdaq: AZN) is a global, science-led biopharmaceutical company that focuses on the discovery, development, and commercialisation of prescription medicines in Oncology, Rare Diseases, and BioPharmaceuticals, including Cardiovascular, Renal & Metabolism, and Respiratory & Immunology. Based in Cambridge, UK, AstraZeneca operates in over 100 countries and its innovative medicines are used by millions of patients worldwide. Please visit astrazeneca.com (http://www.astrazeneca.com/) and follow the Company on Twitter @AstraZeneca (https://twitter.com/AstraZeneca).
Contacts
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