Biotechnology corporations make investments vital time and assets in growing scientific content material for regulatory submissions, educating the scientific group and sufferers, coaching inner groups, and differentiating themselves from opponents. In an period the place misinformation is prevalent, these corporations should swiftly and constantly produce high-quality, focused content material.
Past drug discovery and manufacturing, content material creation is a core exercise throughout numerous departments, together with advertising and marketing, medical affairs, analysis and improvement, regulatory, and pharmacovigilance. Primarily, biotechnology corporations create massive volumes of content material.
Writing high-quality, compliant content material is advanced and demanding, particularly in a extremely regulated trade. There’s usually extra work than accessible personnel, and even when writing is outsourced, it requires time to oversee and evaluate company outputs. Funds constraints and layoffs additional restrict assets for content material improvement.
Writing is only one aspect of the content material improvement workflow. Content material creators should educate themselves, sift by an ever-growing quantity of scientific publications, draft outlines, collaborate with stakeholders, and evaluate drafts. These duties are time-consuming and labour-intensive.
Given these challenges, revolutionary biotechnology corporations, use Synthetic Intelligence (AI) for scientific content material era. AI is just not solely a technological development however a strategic necessity. Because the trade discovers new merchandise, the demand for environment friendly, correct, well timed, and cost-effective content material improvement is essential for achievement.
Generative AI has the potential to revolutionise how scientific knowledge is processed, analysed, and introduced, pushing biotechnology leaders and scientists to rethink their content material era methods.
The position of generative AI in scientific content material era
AI-powered instruments might be utilised in all phases of content material creation, enabling sooner and extra correct era of scientific paperwork. Creating scientific content material manually can take weeks and even months. AI drastically reduces this time by automating repetitive duties and offering data-driven insights that speed up the writing course of.
Additionally Learn:Â Generative AI for sustainability: How these startups are saving the planet with the expertise
For instance, AI can considerably scale back the time wanted to go looking literature databases, draft outlines, and evaluate content material. AI writing assistants are invaluable for paraphrasing, writing titles, checking spelling and grammar, altering tone, producing plain language summaries, seamless quotation era, and language translations—duties which might be usually time-consuming or require exterior experience.
Examples of AI-generated content material in biotech
Biotech corporations can leverage AI to create numerous content material sorts, together with medical research reviews, regulatory submissions, slide displays, posters and abstracts, advertising and marketing supplies, journal articles, medical info letters, coaching supplies, affected person info leaflets, and plain language summaries. Bulletins about utilizing AI for drug discovery generate extra consideration.Â
Nevertheless, corporations are additionally utilizing AI in different areas. Just lately, Moderna introduced a collaboration with OpenAI to combine AI throughout all departments and enterprise processes. Companies that produce medical research reviews and different content material for biotech corporations are additionally adopting AI instruments, additional highlighting its versatility.
Influence of AI on content material creation price
The price of producing scientific content material might be substantial. Creating a slide presentation can price between $20,000 and $60,000 when outsourced to an company. Biotechnology corporations spend tens of millions yearly on content material improvement. AI may also help mitigate these prices by automating many elements of the content material creation course of.
Consultants estimate that generative AI instruments can scale back the time to jot down a medical research report by practically half, bettering the pace of regulatory submissions by 40 per cent, whereas considerably lowering prices throughout regulatory groups.
Furthermore, AI enhances content material high quality by minimising human errors and guaranteeing consistency throughout paperwork. This high quality enchancment can save prices by lowering the necessity for intensive revisions and rework.
Issues about utilizing AI in scientific content material era
A number of considerations should be addressed to make sure the efficient use and adoption of AI instruments in scientific content-generation workflows. These considerations embody accuracy, knowledge security and privateness, the provision of fit-for-purpose options, the price of implementation, and the training curve related to utilizing AI instruments successfully.
AI accuracy: AI methods depend on algorithms and knowledge inputs, which have the potential to result in errors or misinterpretations. Guaranteeing the accuracy of AI-generated content material is essential, significantly in fields requiring precision, equivalent to biotechnology. With human oversight and guided prompts, AI can produce correct outputs corresponding to these of subject material specialists.
Knowledge security and privateness considerations: AI methods require entry to massive datasets, elevating considerations concerning the security of delicate or proprietary info. Firms can mitigate dangers by proscribing AI use to non-sensitive knowledge and using fashions that don’t prepare on proprietary info. Strong knowledge safety measures, like encryption and compliance with privateness laws equivalent to GDPR or HIPAA, are important for safeguarding knowledge.
Match-for-purpose AI options: Generic AI fashions alone are sometimes inadequate for creating life sciences content material. Firms ought to collaborate with life sciences AI distributors to develop tailor-made options that combine into current workflows. Thorough evaluations guarantee AI instruments align with organisational wants and successfully assist content material era processes.
Price of implementation: Deploying AI includes bills for software program, infrastructure upgrades, and upkeep, requiring a cost-benefit evaluation to evaluate ROI. Scalable and cloud-based AI options, together with pilot tasks, can scale back upfront prices and check suitability earlier than full implementation. Most corporations can’t afford bespoke massive language fashions, making scalable options extra sensible.
Coaching and workforce improvement: Profitable AI adoption requires workers to realize abilities by complete coaching packages. Fostering a tradition of steady studying with workshops, on-line programs, and seminars is essential to equipping groups to leverage AI. Cross-functional collaboration and celebrating AI-driven successes can improve adoption and effectiveness.
Job displacement considerations: Whereas AI could exchange sure duties, it can’t replicate human expertise, strategic pondering, or judgment. As an alternative of changing jobs, AI enhances skilled capabilities and creates new alternatives. Staff proficient in AI usually tend to succeed than those that resist leveraging it successfully.
Additionally Learn:Â The rise of generative AI: 6 ASEAN nations main the cost
Embracing AI: The important thing to revolutionising biotechnology’s content material future
Integrating AI in biotechnology content material era presents a transformative alternative to reinforce effectivity, accuracy, and productiveness. Biotechnology leaders and scientists should take proactive steps to combine AI into their content material era workflows.
This includes investing in fit-for-purpose AI options, guaranteeing knowledge privateness and safety, and fostering a talented workforce able to embrace technological developments. By doing so, corporations can enhance effectivity, focus extra on technique and innovation, and preserve a aggressive edge.
The query is not whether or not AI must be used however the way to successfully combine AI into biotechnology content material improvement workflows.
—
Editor’s notice: e27 goals to foster thought management by publishing views from the group. Share your opinion by submitting an article, video, podcast, or infographic.
Be a part of us on Instagram, Fb, X, and LinkedIn to remain related.
Picture credit score: Canva Professional
The submit Past drug discovery: How generative AI is revolutionising content material creation in biotechnology appeared first on e27.
