Category: 3. Business

Jobe Neaser

Tracey Franklin

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Landmark client successes 

•  Liberty Global on its USD3.2bn Sunrise Communications spin-off and dual listing
• Prosus on its EUR4.1bn acquisition of Just Eat Takeaway.com
• Exscientia on its combination with US-based biotech company Recursion
• The lenders on the restructuring of over USD11.5bn in offshore debt for Shimao Group Holdings
• The underwriters on TD Bank’s USD14.6bn exit from Charles Schwab
• The underwriters and funders on the EUR5.8bn debt refinancing of XpFibre
• Uber on a litigation victory in a Securities Exchange Act case against Uber and its officers
• SAP on a litigation victory in connection with the USD12.5bn sale of Qualtrics to Silver Lake Capital 

Innovation leadership – pioneering AI and transforming legal delivery through technology 

The firm continues to advance the boundaries of technology for lawyers. A&O Shearman was the first firm globally to deploy generative AI enterprise-wide when it rolled out Harvey in 2022. ContractMatrix, the firm’s award-winning AI-based contract management platform, is built in collaboration with Harvey and Microsoft. 

In April 2025, the firm began rolling out a suite of agentic AI agents, built in partnership with Harvey, that tackle complex legal workflows. The initial agents focus on antitrust filing analysis, cybersecurity, fund formation, and loan review – high-value areas requiring deep legal expertise and multi-step reasoning. 

A&O Shearman brings this understanding of AI technologies (and the infrastructure used to build them) and real-world AI governance to deliver innovative and uniquely pragmatic advice to clients on managing AI legal risk. The firm has dedicated AI experts in every major jurisdiction across the full risk spectrum and every stage of the AI value chain. The firm counsels numerous tech and industry giants, some of the largest AI foundation model developers, three of the five biggest Western banks in the world, and a G20 country on its national AI strategy and AI regulation.

A&O Shearman has begun FY26 with landmark client wins, including advising Partners Group on its joint acquisition of Techem – the largest M&A transaction in Germany this year; Athora on its GBP5.7bn acquisition of Pension Insurance Corporation Group; Sanmina in its USD3bn acquisition of ZT Systems’ data center business; the lenders on EQT’s USD5.5bn acquisition of Fortnox AB; Froneri on its EUR4.25bn financing; and Sizewell C on its supply chain and contracting strategy for the GBP38bn nuclear project.

The use of artificial intelligence (AI) is rapidly expanding in oncologic clinical practice, with applications including expediting administrative tasks, risk-stratification testing, research, and assistance with interpreting pathology and imaging results.

In order to gain a better understanding of how this technology is currently being applied to practice and where it could be heading in the near future, OncLive® spoke with:

Alicia Morgans, MD, MPH, a genitourinary medical oncologist and the Medical Director of the Survivorship Program at Dana-Farber Cancer Institute, as well as an associate professor of medicine at Harvard Medical School, both in Boston, Massachusetts.

Balazs Halmos, MD, a professor in the Departments of Oncology (Medical Oncology) and Medicine (Oncology and Hematology), and the associate director of Clinical Science at the Montefiore Einstein Comprehensive Cancer Center in New York, New York.

Nitin K. Yerram, MD, the codirector of Urologic Oncology and the director of Urologic Research at Hackensack University Medical Center in New Jersey.

Samina Hirani, MBBS, a hematologist/oncologist at the Mayo Clinic in Eau Claire, Wisconsin.

Alexander Itskovich, MD, the medical director of Oncology Services of the Statesir Cancer Center at Atlantic Health CentraState Medical Center in Freehold, New Jersey.

Ruben Mesa, MD, FACP, the senior vice president of Atrium Health and the president and executive director of Atrium Health Wake Forest Baptist Comprehensive Cancer Center, as well as the vice dean for Cancer Programs and the Charles L. Spurr, MD, Professor of Internal Medicine at Wake Forest University School of Medicine, in Winston-Salem, North Carolina.

“These tools don’t replace the physician’s judgment—they augment it,” Itskovich said. “AI can rapidly sift through massive amounts of data, but the interpretation, clinical decision-making, and patient communication remain firmly in human hands. Together, these technologies are not just making my work more efficient—they’re helping to ensure that fewer clinically significant findings slip through the cracks.”

Significant Time Savings Seen With Administrative Tasks and Patient Communication

Due to its ability to quickly synthesize and organize large datasets, AI is already being used to streamline administrative tasks such as dictation, note taking, and patient monitoring and communication. Examples of these tools include Ambient Voice AI and DAX Copilot.

“Ambient Voice AI allows conversations between patients and clinicians to be securely captured and transformed into medical notes in real time,” Itskovich said. “This technology dramatically reduces the administrative burden of manual notetaking, allowing me to listen more attentively and focus on the patient, rather than writing the note. It’s not just a timesaver; it improves patient engagement and accuracy of documentation.”

“Our institution has been piloting the use of DAX Copilot with good success,” Mesa said. “It listens to my discussion with the patient and generates an editable draft of notes. It learns from the style of my prior notes and gets better and better [with additional use].”

AI Makes a Difference in Risk Stratification and Disease Detection

Multiple investigators in the field of prostate cancer indicated that they are presently using the ArteraAI Prostate Test in their clinical practice. “ArteraAI is a multimodal AI model for [patients with] intermediate-risk localized prostate cancer to help predict whether a patient is likely to benefit from the addition of androgen deprivation therapy [ADT] to their radiation treatment with curative intent,” Morgans explained.

In March 2024, the National Comprehensive Cancer Network included ArteraAI in its updated Clinical Practice Guidelines in Oncology for Prostate Cancer, making it the first AI-enabled predictive and prognostic test to be included in the prostate cancer guidelines.¹ The tool was classified with a Category 2A recommendation and was supported by level 1B evidence from multiple phase 3 clinical trials.

“We are currently using the ArteraAI Prostate Test to improve the risk-stratification of patients who have been recently diagnosed with prostate cancer,” Yerram added. “This tool helps to better individualize patient care and provides patients with a clear path forward regarding treatment, whether that is through surveillance, surgery, or radiation.”

During the 2025 ASCO Annual Meeting, investigators presented findings from an analysis of the ArteraAI Prostate Test v1.2 for identifying patients who could benefit the most from the addition of abiraterone acetate (Zytiga) with or without prednisolone and/or enzalutamide (Xtandi) to standard-of-care ADT the analysis revealed that patients who were identified by ArteraAI as being in the upper risk quartile of risk derived the greatest benefit with the addition of abiraterone in terms of metastasis-free survival, prostate cancer-specific mortality, and distant metastasis.

AI tools are also starting to be adopted for the analysis of imaging and pathology reports. “Machine learning is transforming how we detect and manage incidentalomas—unexpected findings on imaging performed for unrelated reasons. These findings can range from benign cysts to potentially malignant tumors. In the past, incidentalomas in radiology reports could be overlooked due to the sheer volume of imaging that is performed. Now, AI algorithms can scan imaging reports, and any abnormal findings are moved into a specialized workflow that serves as a safety net for our patients,” Itskovich said.

Enhancing and Expediting the Research Processes

Mesa explained that he uses DAX Copilot to create power point slides based on his published research, perform journal article review, and are working to incorporate AI into the clinical trial matching process. Platforms such as OpenEvidence can be used to create tables and figures, ask clinical questions, perform guideline searches, create exam questions, and conduct literature searches.

“I use OpenEvidence commonly, that’s my number 1 go-to, but I [also use] Grok AI for research purposes,” Hirani commented.

Excitement Is Mounting for the Future of AI in the Clinic

Looking ahead, investigators are highly optimistic about the future of AI in the clinical and the potential effect it could have on improving treatment for patients with cancer. As AI technology continues to improve and tools are refined, they will be more integrated into clinical practice, saving investigators time and benefiting patients through enhanced disease detection.

“I believe the future of AI in the clinic is incredibly bright and it will [have an effect] on everything,” Halmos said. “We’re looking at new biomarkers for antibody-drug conjugates aided by AI, as well as its use for lung cancer screening. It could also be used to break down medical jargon for patients and break down language barriers. AI will certainly add an additional tool with utility to our clinics.”

References

1. ArteraAI announced as the first-and-only predictive test for therapy personalization in the 2024 NCCN Guidelines for prostate cancer. News release. ArteraAI. March 4, 2024. Accessed August 15, 2025. https://www.businesswire.com/news/home/20240304893588/en/ArteraAI-Announced-as-the-First-and-Only-Predictive-Test-for-Therapy-Personalization-in-the-2024-NCCN-Guidelines-for-Prostate-Cancer
2. Parker CTA, Liu VYT, Mendes L, et al. Multimodal artificial intelligence (MMAI) model to identify benefit from 2nd-generation androgen receptor pathway inhibitors (ARPI) in high-risk non-metastatic prostate cancer patients from STAMPEDE. J Clin Oncol. 2025;43(suppl 16):5001. doi:10.1200/JCO.2025.43.16_suppl.5001

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‘Privacy disaster’

The Pakistani Rupee (PKR) on Thursday appreciated by 03 paisa against the US Dollar (USD) in the interbank trading and closed at Rs. 281.92 against the previous day’s closing of Rs. 281.95.

However, according to the Forex Association of Pakistan (FAP), the buying and selling rates of the dollar in the open market stood at Rs. 284 and Rs. 284.5, respectively.

The price of the Euro increased by 25 paisa to close at Rs. 328.58 against the last day’s closing of Rs. 328.33, according to the State Bank of Pakistan (SBP).

The Japanese yen went up by 01 paisa and closed at Rs. 1.91, while the exchange rate of the British Pound witnessed a decrease of Rs. 1.07 to close at Rs. 379.74 against the last day’s closing of Rs. 380.81.

The exchange rates of the Emirates Dirham and the Saudi Riyal came down by 01 paisa each to close at Rs. 76.75 and Rs. 75.12, respectively.

Artificial intelligence offers capabilities to streamline research workflows, improve information retrieval accuracy, and distill complex data into meaningful decision-making support across organizations.

Executive summary

Applications of artificial intelligence (AI) are making inroads and headlines in healthcare.
Accordingly, the need for researchers and clinicians to find the latest, most accurate,
clinically relevant information about AI in healthcare (AIH) has grown exponentially.
However, the vast sea of databases from which one can draw often presents
overwhelming noise, requiring users to possess significant expertise in searching and
appraising information.

In contrast, the NEJM Collection published by the NEJM Group, particularly NEJM AI, offers
a guiding light by purposefully curating signals from noise to provide the latest, most
clinically relevant, and immediately transformative information on all AIH topics.

NEJM AI: Transforming healthcare research

AIH is a topic of intense discovery and discussion. Articles alternately spotlight AIH’s
promise or its perils. Many proofs of concept exist for AI-enabled technologies; however,
studies to date on those technologies have been small and sparse. Moreover, patient
outcomes have not been consistently measured, so the effectiveness of the technology
is unclear. The crucial question of performance gain — what measurable improvement is
due to the AI model alone — needs to be rigorously addressed.

The average clinician often struggles to interpret the results of an AI study while trying to
determine whether the tool is safe and effective enough to use in practice, partly due to
the time-intensive nature of appraisal and the sheer volume of new publications.

Medical librarians can bridge the gap

Medical librarians are uniquely positioned to fill those information and skill gaps as
they increasingly field user questions regarding how to find good research on AIH and
interpret the results. AIH information can be drawn from a vast sea of databases, but
the onus is on the user to apply the right filters and be an expert in evaluating the
information. In contrast, the NEJM Complete Collection, including NEJM AI, provides a
guiding light to the latest, most clinically relevant information about AIH. Librarians can
support clinicians not only in searching but also in developing algorithmic literacy and
critically appraising AI outputs, a crucial skill in a rapidly evolving landscape.

The NEJM Complete Collection is a product suite of high-impact, peer-reviewed content
curated for researchers, physician learners, and educators at medical schools. The
collection stands alone as an entire ecosystem that deliberately separates signal
from noise, offering only the most relevant, immediately transformative information
for proactively advancing care. Beyond simply presenting information, the portfolio
curates content for accuracy and clinical relevance, while also offering physician-editor
commentary to provide essential context and clinical decision-making support.

How to optimize the use of the NEJM Collection

For all users, NEJM Journal Watch can serve as the primary entry point for research.
Its authors cull information from more than 150 medical journals, generating succinct
summaries of clinical studies, highlighting key findings and clinical implications, and
providing expert commentary. This effectively offloads the overwhelming task of staying
current and appraising diverse literature for clinicians and researchers. Topics can then
be explored in more depth within the primary articles.

Complementary publications

The journals in the NEJM Complete Collection are designed to complement each other,
each with a distinct and necessary mission aligned towards specific improvements in
research and medicine, rather than merely increasing publication volume. Consider this
AIH example: