Rishi Sunak wins first round of Conservative Party leadership vote in UK
London(PTI): Former Chancellor Rishi Sunak extended his lead in the UK prime ministerial race on Wednesday with the highest number of votes at 88 in the first round of voting by Conservative Party MPs, which narrowed down the race from eight to six candidates on the shortlist.
Fellow Indian-origin candidate, Attorney General Suella Braverman, features last on the latest tally with 32 votes, behind Trade Minister Penny Mordaunt (67 votes), Foreign Secretary Liz Truss (50 votes), former minister Kemi Badenoch (40 votes) and backbencher Tom Tugendhat (37 votes).
Newly appointed Chancellor Nadhim Zahawi and former Cabinet minister Jeremy Hunt are out of the race after not being able to attract the requisite votes of at least 30 MPs, at 25 and 18 backers respectively.
While Sunak has maintained a steady lead among his Tory parliamentary colleagues since he declared his intention to run for party leadership last week, the Conservative Party membership base which will have the final say seems to be building momentum behind Penny Mordaunt.
At this early stage of the contest, the race seems to be narrowing down into a three-way Sunak, Mordaunt and Liz Truss clash, but the field is still seen as wide open.
The next round of voting by the 358 Conservative members of Parliament to pick their favourites left on the ballot paper is scheduled for Thursday, when the field of candidates will be narrowed down even further to a shorter list of finalists.
Under the timetable set by the 1922 Committee of Tory backbenchers, the deadline to whittle down the shortlist to just two remaining candidates is July 21.
The process will then be taken over by the Conservative Party headquarters to organise a series of hustings in different parts of the UK for the final two to pitch their campaign pledges to the estimated 200,000 Conservative Party membership.
The candidate who receives the most votes will be elected the new Conservative Party and British Prime Minister leader on September 5.
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Jamia prof receives Rs 94 lakh grant to formulate AI-driven drug to treat breast cancer
New Delhi (PTI): An associate professor at Jamia Millia Islamia has been awarded a research grant of approximately Rs 94 lakh by the prestigious ICMR to support research in leveraging Artificial Intelligence for treatment of breast cancer.
The Indian Council of Medical Research (ICMR) has granted funding to Raza to develop cutting-edge tools for AI-guided drug design, focusing on optimising drug compounds, identifying therapeutic targets, and formulating novel treatment strategies for breast cancer, a statement by the varsity said on Friday.
One such promising drug compound 'DdpMPyPEPhU' already patented by Raza will be further explored under this initiative, the statement said.
This research will address critical challenges in breast cancer treatment and is expected to yield transformative outcomes that could impact healthcare practices globally, it added.
The three-year funding will facilitate advanced experimentation, foster collaboration with leading experts, and accelerate the development of innovative solutions for breast cancer treatment.
Jamia Vice-Chancellor Mazhar Asif and Registrar Md. Mahtab Alam Rizvi congratulated Raza on this accomplishment.
Asif stated, “This is a moment of immense pride for JMI. Raza’s recognition by ICMR underscores the university’s commitment to fostering research excellence and innovation. His groundbreaking work showcases JMI’s vital contributions to integrating AI in healthcare research.”
Expressing gratitude for the recognition, Raza said, “I am deeply honoured to receive this grant from ICMR. It represents a tremendous opportunity to advance our research on AI- driven drug design and contribute to better health outcomes for millions. I am thankful to my research team, collaborators and ICMR for their unwavering support.”
Raza is known for his research in the application of AI in healthcare, focusing on designing and optimising drug compounds through AI-based multitarget docking, molecular simulations, and genomics-driven personalised medicine.
