DIRECTOR OF CLINICAL PHARMACOLOGY
San Francisco, California / $200000 - $220000
$200000 - $220000
San Francisco, California
DIRECTOR OF CLINICAL PHARMACOLOGY
BAY AREA - HYBRID 2-3 DAYS IN OFFICE
As a Director of Clinical Pharmacology, you will be responsible for leading and executing the clinical pharmacology strategy across various phases of drug development to support successful regulatory filings and marketing approval. This role requires strong leadership, excellent communication and collaboration skills, and deep expertise in clinical pharmacology.
* Provide strategic direction and leadership to clinical pharmacology activities across the drug development programs.
* Liaise with cross-functional stakeholders, including clinical development, biostatistics, translational medicine, and regulatory affairs, to ensure seamless execution of the clinical pharmacology programs.
* Manage external vendors and partners, including clinical research organizations (CROs) and academic institutions, as needed to support clinical pharmacology activities.
* Ensure compliance with regulatory requirements related to clinical pharmacology and drug development.
* Develop clinical pharmacology study protocols and oversee the conduct of clinical pharmacology studies, including pharmacokinetic, pharmacodynamic, and drug-drug interaction studies.
* Design, analyze and interpret clinical pharmacology trials and integrate data into development plans.
* Generate and/or review clinical pharmacology reports, including study reports, clinical pharmacology sections of investigational new drug applications (INDs), and new drug applications (NDAs).
* Collaborate with clinical development teams to implement appropriate drug-drug interaction strategies.
* Communicate clinical pharmacology results and implications in a clear and concise manner to internal and external stakeholders, including regulatory agencies, partners, and senior leadership.
SKILLS AND QUALIFICATIONS:
* Advanced degree (PhD or PharmD) in clinical pharmacology, pharmacokinetics, or related field with at least 10 years of experience in clinical pharmacology.
* Demonstrated experience in leading clinical pharmacology programs and teams across various phases of drug development.
* Strong analytical skills with experience in designing, analyzing, and interpreting clinical pharmacology trials.
* In-depth knowledge of regulatory requirements related to clinical pharmacology and drug development, including IND and NDA filings.
* Excellent verbal and written communication skills with the ability to present complex data to both technical and non-technical audiences.
* Strong project management skills and ability to prioritize and manage multiple projects simultaneously.
* Experience in managing external vendors, CROs, and academic institutions.
* Previous experience in oncology or hematology indications is a plus.
Weekly News Digest: August 1st – 5th | Harnham Recruitment post
This is Harnham’s weekly news digest, the place to come for a quick breakdown of the week’s top news stories from the world of Data & Analytics.
TOWARDS DATA SCIENCE: HOW TO PREPARE FOR BIG TECH DATA SCIENCE INTERVIEWS
Big tech interviews don’t have to be intimidating if you know how to prepare properly. With so many big tech companies focusing more on cloud technologies, many data scientists are targeting the likes of Meta, Amazon, Netflix, and Google for their first jobs in the industry. While candidates will understandably have some apprehension around their interview with such companies, they are not that different from other interviews. Most big tech companies have similar interviewing practices. They are simply more selective than others which results in high rejection rates. Consequently, you don't need to worry about ‘impossible’ questions when preparing for these interviews. Instead, you should concentrate on the typical technical interview questions, paying close attention to how you will differentiate yourself from the hundreds of other highly competent applicants for the same profession. Get ahead of your interviews with a personal strategy that helps you play to your strengths and avoid your weaknesses by having a thorough understanding of how a company organises, plans, and evaluates interviews. Towards Data Science shares the following tips to remember during the interview process with big tech companies: Learn the realities and competitive landscapeData science skills are nothing without real-world problem-solving skillsYour competitors will probably have several years of industry experience and the educational qualifications to matchIf you’re making a career change, the hardest part of the process will be getting a foot in the doorChoose your learning resourcesDetermine how you will stand out during the interview process To read more about this, click here.
LABIO TECH: WHY BIOSTATISTIONS ARE ESSENTIAL FOR SUCCESSFUL CLINICAL TRIAL MANAGEMENT
Biostatisticians’ responsibilities go beyond simply analysing data at the end of a clinical study – they’re involved in the management of the clinical trial from day one in order to maximise the possibility of new treatments being authorised for the market. Overseeing these clinical trials means they have a long to-do list. They make recommendations for trial design, choose the right sample size, and ensure that the patients who are enrolled are randomised fairly. They provide definitions for data analysis, help define endpoints, and create tables and graphics for the clinical study report. “People often think that biostatistics comes in at the end of a clinical trial, but this can lead to a lot of issues, for example, when you find out too late about missing data or incorrect randomization,” said Malin Schollin, Director of Biostatistics at LINK Medical, a Swedish contract research organisation. “There is great value in having a statistician on board during the entire project because then we can take part in the decision making, and help assess how it will affect analyses, evaluation, or results.” To read more about this, click here.
ANALYTICS INSIGHT: TOP FIVE PYTHON DATA SCIENCE MINI PROJECT
Data Science uses Python to deal with massive amounts of data every single day. Many students are interested in data science and, in the same vein, work on a variety of mini projects based on data science using Python. Data science is a discipline that assists us in extracting knowledge and information from many sorts of structured or unstructured data. Here are five python Data science mini projects to explore. Real-time audio analysis – This will pique the curiosity of music enthusiasts by allowing you to perform real-time audio analysis with the Fast Fourier Transform tool, which is a crucial skill set for a data scientist. Color Detector – Determine all colour hues from a given image or video, whether it is black and white or colour. This can be quite useful for investigating officials and in the industry! Banking fraud detections – Detect credit card fraud utilising data science principles such as decision trees, neural networks, and logistic regression. Real-time image animation – Deal with visual expression dependent on camera position. This involves the use of data science in conjunction with computer vision. Business Advisor software using data science – One of the most intriguing projects because it employs exploratory data analysis, in which the programme automatically analyses the data, raises questions, and then displays facts and solutions in the form of visual graphs and other charts. To read more about this, click here.
TOWARDS DATA SCIENCE: WOULD YOU LIKE TO BECOME A BETTER DATA SCIENTIST?
START WRITING ARTICLES Data is all around us; we all generate massive amounts of data every day. Yet non-technical individuals have no idea what data is or why it is so valuable. That is why, in every presentation, a data scientist must educate their audience. You may be required to describe the data, explain how you intend to utilise it to construct a model, and present your findings. You can’t do this without critical skills in writing and communication. Businesses have a tonne of data and they need data scientists who can share their insights with others, while also understanding and using this data. Sometimes people with technical expertise aren't the best communicators, which is where strong writing skills can be especially useful. Writing can help you transmit ideas effectively. Once you become good at writing, explaining your ideas in a presentation or meeting will become more natural and fluent. When writing an article, you become more aware of your work. You can spot weak points and discover sections that need more research or could be a new topic for another article. So, believe it or not, writing can help you improve your communication skills and learn more about the field of data science. To read more about this, click here. We've loved seeing all the news from Data & Analytics in the past week, it’s a market full of exciting and dynamic opportunities. To learn more about our work in this space, get in touch with us at email@example.com.
DevOps: The Cure To Pharma’s Problem? | Harnham Recruitment post
DevOps quite literally does what it says on the tin, a streamlined partnership of development and operations which gives companies the tools to deliver much faster services. Removing the usual barriered siloes between the two divisions, not only is DevOps more efficient than its traditional counterparts, but the increased coordination and collaboration provided within DevOps undoubtedly produces much stronger, more reliable products. As mentioned in one of our previous articles, the DevOps market is one that has seen unprecedented growth and is forecasted to continue doing so for the foreseeable future. Its benefits are second-to-none, from ensuring the smooth-running of processes to increasing levels of productivity, DevOps’ autonomous nature reduces, and in some cases eradicates, many of the pain points businesses face.However, not all industries have been quick to adopt this transformative specialism. Pharmaceuticals is one key example, with many companies citing security as their main concern for choosing not to adopt the technology. In the US alone, data breaches in the healthcare industry cost $5.6 billion every year, and the infamous attack on the UK’s NHS by hacker group, The WannaCry, cost £92m alone. Nevertheless, as the industry begins to understand the key areas where it is most at risk of breaches, such as its complex supply chain and current use of outdated devices due to the longevity of many companies, changes and updates are being made to make DevOps adoption more secure. But why is it so important that the industry adopts DevOps? Here are three key reasons:Improved efficiency of clinical trialsIt can take up to 10 years for a new drug to come to market, and the longest part of the process is, more often than not, the clinical trials which can take anywhere between six to seven years to complete.However, certain elements of DevOps, such as the use of the cloud for data collection, can improve the efficiency of this process ten-fold. When used alongside technology such as wearable devices and electronic diaries, the collection and analysis of crucial data, such as a trial participants vitals, can be done in real-time from anywhere and everywhere. Cheaper product creationThe pharmaceutical industry is heavily regulated to ensure that the drugs created do not cause harm, and this includes monitoring its software and hardware components as much as anything else.Using Computer System Validation (CSV) is the most common way of companies being regulated by the FDA, but there’s no denying that this system is time-consuming and expensive. Using DevOps for this process allows businesses to autonomously reduce the risk of bugs, avoid bottlenecking all without damaging productivity and reliability. Not only do all these elements within DevOps mean the regulation process becomes far more streamlined, but regulations are more likely to be adhered to and products are able to be taken to market much faster, improving ROI and revenue. Reduce complexity of big-data deploymentAs of 2020, it was reported that there were 2,314 exabytes of healthcare data globally. This huge amount of insight provides a goldmine of information for pharmaceutical companies but the task of sifting through it manually to spot trends, improve upon patient care and explore new avenues for drug creation is impossible. The implementation of DevOps not only accelerates the process of scouring this data but improves our ability to spot threats on the horizon and makes drug development much cheaper. As suggested in Healthcare, “The ability to leverage DevOps in the analysis of big data healthcare sets can help providers reduce treatment costs, predict outbreaks of epidemics, avoid preventable diseases and improve patient quality of care and outcomes.’’Of course, where technology is involved, there is no way to completely eradicate risk. Pharma must look carefully at how a fine line can be struck between implementing DevOps and keeping patient data safe. However, as the ability of security systems greatly improves over time, it is very likely that we will see more and more Life Science and Pharmaceutical businesses adopting and reaping the rewards from DevOps. To learn more about the roles we currently have available in the take a look at our devops jobs or get in touch with one of our expert consultants to find out more.
The Biggest Anticipated Data Science Trends In Healthcare | Harnham Recruitment post
Data Science and Analytics have been the backbone of society, both nationally and internationally, during the past 18 months. Detailed analysis of huge data sets has helped businesses of all shapes and sizes overcome some of the largest challenges the pandemic has created.From enabling staff to work from home to predicting the next potential strain of the COVID-19 virus – Data & Analytics has undoubtedly been the difference between survival and failure. According to research by McKinsey, digital or digitally enabled products used by executives have accelerated by seven years in order to respond quickly and efficiently to the crisis. One industry that has seen vast change in terms of embracing Data Science & Analytics tools and methods is healthcare. Traditionally, this industry has been slow to implement any sort of technological change however, over the past year and a half, it has become clear that it must evolve, and fast. Responding to crises, such as the pandemic, has been no easy feat for anyone within the healthcare sector, but those who had previously invested in, or rapidly turned to, data science trends such as AI and DevOps have reaped the rewards. Here are three movements we have seen creeping into our healthcare systems in recent times, and ones which we will undoubtedly see more of over the next six to 12 months. Increased use of AI to help make care more efficientThere is huge potential for AI and Data Science to have a sizeable, positive impact in healthcare soon. One example is using machine learning to optimise patient procedures, ensuring they’re in and out as efficiently as possible consequently freeing up bed space and allow for more operations to be undertaken – a problematic issue for the NHS currently. AI is also being used to help diagnose illnesses. Using computer vision and deep learning to understand images from scans, those illnesses that can be harder to detect, such as certain types of cancers, can be found and treated a lot earlier, meaning a much higher rate of survival for patients.In many cases and tests that have been done, AI has been more successful than using a doctor with several years’ experience.Implementation of the cloud for clinical trialsIt can take up to 10 years for a new drug to come to market, and the longest part of the process is often the clinical trials.However, certain elements of Data Science, such as the use of the cloud for data collection, can improve the efficiency of this process ten-fold. When used alongside technology such as wearable devices and electronic diaries, the collection and analysis of crucial data, such as a trial participants vitals, can be done in real-time from anywhere and everywhere. Adopting DevOps for cost reductionThe healthcare industry is heavily regulated to ensure that the drugs created do not cause harm, and this includes monitoring its software and hardware components as much as anything else.Using Computer System Validation (CSV) is the most common way of companies being regulated by the FDA, but there’s no denying that this system is time-consuming and expensive. Using DevOps for this process allows businesses to autonomously reduce the risk of bugs and avoid bottlenecking all without damaging productivity and reliability. Not only do all these elements within DevOps mean the regulation process becomes far more streamlined, but regulations are more likely to be adhered to and products are able to be taken to market much faster, improving ROI and revenue.Data Science tools have been, and will continue to be, the main driver of change within healthcare. From making medical processes more efficient to reducing the cost of HealthTech, improving productivity, and anticipating big potential changes within the sector, the importance of Data & Analytics has never been clearer.If you’re looking for your next role, or are looking to build out your Data Science team, Harnham can help. Take a look at our latest data science jobs or get in touch with one of our expert consultants to find out more.
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