AIkido Pharma Notes Advancement in Radiopharmaceutical Research

On April 16, 2021 AIkido Pharma Inc. (Nasdaq: AIKI) ("AIkido" or the "Company") reported that a recent study announced positive early results from a PSMA 617-Lu177 study conducted by a leading global pharmaceutical company (Press release, AIkido Pharma, APR 16, 2021, View Source [SID1234578130]). The report provides strong indications for analogous success in similar technology the Company is helping to develop.

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Anthony Hayes, CEO of AIkido Pharma, stated, "As a rising tide lifts all boats, these results indicate the strength of our prior investment in this technology field. These early reports indicate there is strong evidence that developing radioligand therapies have the potential to be an alternative cancer treatment and provide positive outcomes for patients with advanced prostate cancer. The Company’s stock price has been down recently, but we believe these positive results from the Novartis Phase III study provides an incremental proof point that reinforces our confidence in the radiopharmaceutical space, PSMA and our investment in this technology. With testing data for our technology expected in Q2 of this year, we are excited about the results and the advancement of this technology."

Castle Biosciences Presents Data at the 10th World Congress of Melanoma and 17th European Association of Dermato-Oncology Congress

On April 16, 2021 Castle Biosciences, Inc. (Nasdaq: CSTL), a skin cancer diagnostics company providing personalized genomic information to improve cancer treatment decisions, reported that data on its three skin cancer gene expression profile tests at the 10th World Congress of Melanoma and 17th European Association of Dermato-Oncology (EADO) Congress (Press release, Castle Biosciences, APR 16, 2021, View Source [SID1234578128]).

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DecisionDx-Melanoma:

DecisionDx-Melanoma is Castle’s gene expression profile test that uses an individual patient’s tumor biology to predict risk of cutaneous melanoma metastasis or recurrence, as well as sentinel lymph node (SLN) positivity, independent of traditional staging factors. Castle presented data on DecisionDx-Melanoma with two virtual posters. The first is a late-breaking abstract, titled "Integration of the 31-gene expression profile test with clinicopathologic features (i31-GEP) to assess sentinel lymph node positivity risk in patients with cutaneous melanoma." More details can be found here in the Company’s news release from April 15, 2021.

A second poster entitled "Using a 31-gene expression profile test to stratify patients with sentinel lymph node negative stage I-II cutaneous melanoma according to recurrence risk: Longer-term follow-up from a prospective, multicentre study" was also presented. This poster can be found here.

Study methods and findings:

Interim data from an independent, prospective multicentre Spanish cohort was previously published.
This poster provided long-term performance data (median follow-up 3.9 years) of 86 primary melanoma tumors from patients staged I-II at diagnosis according to the American Joint Committee on Cancer (AJCC) 7th edition criteria with negative SLN biopsy (SLNB) results, which were tested with DecisionDx-Melanoma.
Significantly different risk profiles (p=0.005) with respect to disease-free survival (DFS) were maintained between groups with:
3-year Disease-Free Survival for Class 1A = 100%
3-year Disease-Free Survival for Class 1A, 1B/2A = 91%
3-year Disease-Free Survival for Class 2B = 75%
Patients with a DecisionDx-Melanoma Class 2B result had three times the odds of recurrence relative to those with a Class 1A result.
Distant metastasis was not observed in the Class 1A group, while 75% occurred in the high-risk Class 2B group.
The study authors conclude that DecisionDx-Melanoma significantly differentiates recurrence risk in SLN negative patients, which may allow for better resource allocation to patients at the highest risk of melanoma recurrence.
DecisionDx-SCC:

DecisionDx-SCC is Castle’s prognostic gene expression profile test for patients diagnosed with high-risk cutaneous squamous cell carcinoma (SCC) designed to use a patient’s tumor biology to predict individual risk of metastasis for patients with SCC and one or more risk factors. Castle presented data on DecisionDx-SCC with two virtual posters. Both posters highlight studies in which the 40-gene expression profile test demonstrated the ability to accurately classify risk for metastasis in SCC patients with one or more risk factors.

The first poster is entitled "Incorporation of a prognostic 40-gene expression profile (40-GEP) test into clinicopathological risk assessment using newly published guidelines for cutaneous squamous cell carcinoma (cSCC)." The poster can be found here.

Study methods and findings:

The National Comprehensive Cancer Network (NCCN) published updated SCC guidelines in 2021, now categorizing local SCC into three groups: low risk, high risk and very high risk. This study was performed to assess the performance of DecisionDx-SCC within these new NCCN guidelines.
420 primary SCC archival tumor specimens with one or more associated risk factors and known three-year outcomes were collected, tested with DecisionDx-SCC and analyzed using Kaplan Meier and Cox multivariate regression analysis. All patients in this cohort were classified as high risk or very high risk by the new National Comprehensive Cancer Network (NCCN) framework.
Importantly:
DecisionDx-SCC provided significant stratification within both the NCCN high-risk group (p=0.0001) and the NCCN very high-risk group (p<0.0001).
Multivariate Cox regression analysis showed that both the DecisionDx-SCC Class 2A (p<0.001) and Class 2B (p<0.001) were independent and stronger predictors of metastasis when compared to NCCN groups (Class 2A hazard ratio = 2.92; Class 2B hazard ratio = 9.50; NCCN very high-risk hazard ratio = 1.99).
These data show that DecisionDx-SCC provides further stratification for the risk of metastasis within high-risk and very high-risk SCC sample groups.
The study validated that DecisionDx-SCC adds independent prognostic value within the new NCCN guidelines and could be applied as an adjunct to enhance SCC risk stratification and found that incorporating DecisionDx-SCC into SCC patient risk assessment could lead to more personalized and risk-appropriate pathways for improvement of patient management and disease related outcomes.
The second DecisionDx-SCC poster is entitled "Real-world clinical usage data demonstrates appropriate utilization of the prognostic 40-gene expression profile test for cutaneous squamous cell carcinoma with one or more risk factors." The poster can be found here .

Study methods and findings:

Summary metrics were generated on the first 1000 samples received for DecisionDx-SCC testing that met clinical testing criteria. Metrics on early clinical usage include:
69.0% of samples received DecisionDx-SCC Class 1 results, 26.0% received DecisionDx-SCC Class 2A results and 1.3% received DecisionDx-SCC Class 2B results.
Technical reliability of DecisionDx-SCC was 96.3%.
Most tested patients had three or more risk factors.
DecisionDx DiffDx-Melanoma:

DecisionDx DiffDx-Melanoma is designed to aid dermatopathologists in characterizing difficult-to-diagnose melanocytic lesions. DecisionDx DiffDx-Melanoma classifies these lesions as benign, intermediate-risk or malignant.

Two virtual posters highlighted studies in which DecisionDx DiffDx-Melanoma demonstrated the ability to refine diagnoses of difficult-to-diagnose melanocytic lesions.

The first poster is entitled "Performance of a diagnostic 35-gene expression profile test (GEP) on difficult-to-diagnose melanocytic lesions." The poster can be found here.

Study methods and findings:

DecisionDx DiffDx-Melanoma’s performance was evaluated in its target difficult-to-diagnose population, which included lesions of unknown malignant potential (UMP) and diagnostically discordant lesions.
In a cohort of 65 difficult-to-diagnose melanocytic lesions, the test provided a result in 100% of lesions, (i.e., no technical failures).
DecisionDx DiffDx-Melanoma provided an actionable result in 97% of these difficult-to-diagnose lesions, as only 2 cases received an intermediate result.
DecisionDx DiffDx-Melanoma’s previously published accuracy metrics in lesions with diagnostic concordance has been shown to alleviate uncertainty in difficult-to-diagnose lesions leading to recommendations for decreased unnecessary procedures while appropriately identifying at-risk patients.
The second DecisionDx DiffDx-Melanoma poster is entitled "Development, Validation, and Clinical Utility of the 35-Gene Expression Profile Test for Use as an Adjunctive Melanoma Diagnostic Tool." The data therein was previously published in SKIN: The Journal of Cutaneous Medicine. The poster can be found here.

Study methods and findings:

DecisionDx DiffDx-Melanoma was developed using artificial intelligence methods trained on 200 benign nevi and 216 melanomas to select a panel of 32 discriminant and 3 control genes.
The test’s ability to differentiate accurately between benign and malignant pigmented skin lesions was characterized.
The test provides a modest intermediate-risk zone of 3.6% and a high technical success rate at 96.6%.
The analytical validity data of the DecisionDx DiffDx-Melanoma test demonstrates high precision as an indication of technical success.
Dermatopathologists utilized the DecisionDx DiffDx-Melanoma result to refine their diagnoses and their diagnostic confidence increased by 51%.
Dermatologists utilized the DecisionDx DiffDx-Melanoma result, which led to altered treatment plans including re-excisions in agreement with the DecisionDx DiffDx-Melanoma result.
About DecisionDx-Melanoma

DecisionDx-Melanoma is a gene expression profile test that uses an individual patient’s tumor biology to predict individual risk of cutaneous melanoma metastasis or recurrence, as well as sentinel lymph node positivity, independent of traditional staging factors, and has been studied in more than 5,700 patient samples. Using tissue from the primary melanoma, the test measures the expression of 31 genes. The test has been validated in four archival risk of recurrence studies of 901 patients and six prospective risk of recurrence studies including more than 1,600 patients. To predict likelihood of sentinel lymph node positivity, the Company utilizes its proprietary algorithm, i31-GEP, to produce an integrated test result. i31-GEP is an artificial intelligence-based neural network algorithm (independently validated in a cohort of 1,674 prospective, consecutively tested patients with T1-T4 cutaneous melanoma) that integrates the DecisionDx-Melanoma test result with the patient’s traditional clinicopathologic features. Impact on patient management plans for one of every two patients tested has been demonstrated in four multicenter and single-center studies including more than 560 patients. The consistent performance and accuracy demonstrated in these studies provides confidence in disease management plans that incorporate DecisionDx-Melanoma test results. Through December 31, 2020, DecisionDx-Melanoma has been ordered more than 68,920 times for use in patients with cutaneous melanoma.

More information about the test and disease can be found at www.CastleTestInfo.com.

About DecisionDx DiffDx-Melanoma

DecisionDx DiffDx-Melanoma is designed to aid dermatopathologists in characterizing difficult-to-diagnose melanocytic lesions. Of the approximately 2 million suspicious pigmented lesions biopsied annually in the U.S., Castle estimates that approximately 300,000 of those cannot be confidently classified as either benign or malignant through traditional histopathology methods. DecisionDx DiffDx-Melanoma classifies these lesions as: benign (gene expression profile suggestive of benign neoplasm); intermediate-risk (gene expression profile cannot exclude malignancy); or malignant (gene expression profile suggestive of melanoma). Interpreted in the context of other clinical, laboratory and histopathologic information, DecisionDx DiffDx-Melanoma is designed to add diagnostic clarity and confidence for dermatopathologists while helping dermatologists deliver more informed patient management plans.

More information about the test and disease can be found at www.CastleTestInfo.com.

About DecisionDx-SCC

DecisionDx-SCC is a 40-gene expression profile test that uses an individual patient’s tumor biology to predict individual risk of cutaneous squamous cell carcinoma metastasis for patients with one or more risk factors. The test result, in which patients are stratified into a Class 1, 2A or 2B risk category, predicts individual metastatic risk to inform risk-appropriate management.

Peer-reviewed publications have demonstrated that DecisionDx-SCC is an independent predictor of metastatic risk and that integrating DecisionDx-SCC with current prognostic methods can add positive predictive value to clinician decisions regarding staging and management.

Moderna to Report First Quarter Financial Results on Thursday, May 6, 2021

On April 16, 2021 Moderna, Inc. (Nasdaq: MRNA), a biotechnology company pioneering messenger RNA (mRNA) therapeutics and vaccines, reported that it will host a live conference call and webcast at 8:00 a.m. ET on Thursday, May 6, 2021 to reports its first quarter 2021 financial results, and provide a corporate update (Press release, Moderna Therapeutics, APR 16, 2021, View Source [SID1234578127]).

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To access the live conference call, please dial 866-922-5184 (domestic) or 409-937-8950 (international) and refer to conference ID 7487119. A webcast of the call will also be available under "Events and Presentations" in the Investors section of the Moderna website at investors.modernatx.com. The archived webcast will be available on Moderna’s website approximately two hours after the conference call and will be available for one year following the call.

Arrowhead Pharmaceuticals to Webcast Fiscal 2021 Second Quarter Results

On April 16, 2021 Arrowhead Pharmaceuticals Inc. (NASDAQ: ARWR) reported that it will host a webcast and conference call on May 4, 2021, at 4:30 p.m. ET to discuss its financial results for the fiscal second quarter ended March 31, 2021 (Press release, Arrowhead Pharmaceuticals, APR 16, 2021, View Source [SID1234578126]).

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Conference Call and Webcast Details

Investors may access a live audio webcast on the Company’s website at View Source For analysts that wish to participate in the conference call, please dial 855-215-6159 or 315-625-6887 and provide Conference ID 3080187.

A replay of the webcast will be available on the company’s website approximately two hours after the conclusion of the call and will remain available for 90 days. An audio replay will also be available approximately two hours after the conclusion of the call and will be available for 3 days. To access the audio replay, dial 855-859-2056 or 404-537-3406 and provide Conference ID 3080187.

Relay Therapeutics Extends Leadership in Integrating Computational and Experimental Approaches to Create Precision Medicines by Acquiring ZebiAI

On April 16, 2021 Relay Therapeutics, Inc. (Nasdaq: RLAY), a clinical-stage precision medicine company transforming the drug discovery process by combining leading edge computational and experimental technologies, reported the acquisition of ZebiAI, a pioneer in applying massive experimental DNA encoded library data sets to power machine learning for drug discovery (ML-DEL) (Press release, Relay Therapeutics, APR 16, 2021, View Source [SID1234578125]). Together, Relay Therapeutics and ZebiAI aspire to accelerate the application of machine learning across the Dynamo platform to potentially fast-track the finding of novel medicines against intractable targets.

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Relay Therapeutics’ experienced team, leadership, and track record of integrating leading edge computational and experimental technologies positions the company as a strategic partner of choice for emerging technologies and founders in these fields. ZebiAI is the first of such technologies that will augment the Dynamo platform, and Relay Therapeutics looks forward to further investments in these areas.

At its core, Relay Therapeutics’ approach is to continually enhance the drug discovery process by accumulating purpose-built experimental data sets at each point along the discovery continuum and deploy them to strengthen the predictive power of proprietary computational tools. ZebiAI builds on Relay Therapeutics’ approach by bringing a massive library of curated experimental data, validated machine learning models, a collaboration with Google’s Accelerated Science Group to continue to build this computational capability, as well as a team with deep expertise in ML-DEL.

"We are excited to welcome the ZebiAI team into Relay Therapeutics," said Sanjiv Patel, M.D., president and chief executive officer of Relay Therapeutics. "We have built a unique ability over the past five years to combine diverse computational and experimental technologies to create new medicines. The combination of ZebiAI’s approach with our Dynamo platform has the potential to predict more drug-like chemical starting points, reduce cycle time to compound optimization, and ultimately, increase the number and range of programs that can be developed in parallel. We aim to continue to tackle the toughest drug discovery problems to have an even greater impact on patients, and ZebiAI will help us achieve this goal."

"We believe the combination of Relay Therapeutics’ proven track record of integrating computational and experimental technologies to bring medicines into clinical development with ZebiAI’s extensive experimental data sets and ML-DEL capabilities will push the boundaries of what is possible in drug discovery," said Rafael Gomez-Bombarelli, Ph.D., chief learning officer of ZebiAI and assistant professor at Massachusetts Institute of Technology who will join Relay Therapeutics as an advisor.

Under the terms of the merger agreement, Relay Therapeutics will pay $85 million upfront, comprised of $20 million in cash and $65 million in Relay Therapeutics common stock. ZebiAI stockholders are also eligible to receive up to an additional $85 million in platform and program-related milestone payments, payable in Relay Therapeutics common stock. Additionally, if Relay Therapeutics enters partnering or collaboration agreements related to ZebiAI’s platform, ZebiAI stockholders are eligible to receive 10% of the payments received within the next three years, up to an aggregate cap of $100 million payable in cash. The acquisition is subject to customary closing conditions. Upon closing of this acquisition, Relay Therapeutics continues to expect its current cash and cash equivalents will be sufficient to fund its current operating plan into 2024.

Conference Call Information

Relay Therapeutics will host a live webcast and conference call today beginning at 8:00 a.m. ET to discuss the ZebiAI acquisition. To access the live call, please dial (833) 540-1168 (domestic) or (929) 517-0359 (international) and refer to conference ID 7827289. A webcast of the conference call will be available under "News and Presentations" in the Media & Investors section of Relay Therapeutics’ website at View Source The archived webcast will be available on Relay Therapeutics’ website approximately two hours after the conference call and will be available for 30 days following the call.