DEV Community: Newpage Solutions

The True Cost of Developing Software in Life Sciences

Newpage Solutions — Fri, 12 Dec 2025 09:40:49 +0000

In life sciences, software is more than just a tool - it's the backbone of innovation. From AI-driven precision medicine to the infrastructure that powers clinical trials, digital solutions connect people, processes, and data. But when it comes to budgeting for software, the question isn't simple: how much does it really cost to build solutions today?

The answer depends on several factors. Regulatory compliance, integrations, complexity, and scalability all play a major role. Projects in pharma and healthcare are rarely just about code - they involve audits, validation, secure data handling, and seamless integration with systems like EHRs, LIMS, and ERP platforms. Each layer adds to the total investment.

Feature scope is an obvious driver of cost. A basic mobile app for patients is much less expensive than a full clinical trial management system. Architecture and tech choices matter too. Traditional monolithic systems are cheaper than cloud-native solutions that rely on AI or microservices. Then there's team composition. You need more than developers - project managers, UX/UI designers, data scientists, and domain experts all contribute to quality, compliance, and speed. Post-launch support, updates, and security fixes add another layer of ongoing costs.

In real terms, budgets can vary widely. A digital health companion app may range from $50,000 to $150,000, depending on features. Clinical trial management software often costs between $300,000 and $1 million due to compliance and role-based access requirements. AI-driven platforms for precision medicine easily start at $1 million, factoring in infrastructure, AI models, and validation testing.

Costs don't stop at development. Scope creep, unexpected technical challenges, regulatory reviews, and scalability requirements can inflate budgets. Hiring specialized talent in areas like bioinformatics or AI can be a limiting factor. Post-launch maintenance is often underestimated, yet it is critical for long-term success.

Planning early and strategically can control these costs. Start with a minimal viable product to validate ideas. Use modular, cloud-based designs for scalability. Leverage CI/CD pipelines and automated testing to speed up releases and reduce errors. And always reserve 15 to 25 percent of your budget for the unexpected.

Ultimately, cost management in life sciences software development isn't just about money. It's about creating solutions that are reliable, compliant, and scalable while ensuring speed and quality. Success depends on meticulous planning, domain knowledge, and the right development partner.

At Newpage, we specialize in building high-quality, compliant software for healthcare and life sciences companies. Whether it's an AI analytics platform, a clinical trial application, or a patient app, we bring the right mix of skills and experience to ensure your project delivers results.

In our latest blog, we explore what goes into building software for life sciences today, the factors that drive costs, and how companies can plan effectively to avoid surprises.

Read the full article here: https://newpage.io/resources/blogs/the-cost-of-developing-a-software-today/

Life Sciences Need More Than Tech Skills - they Need Domain-Ready Talent

Newpage Solutions — Fri, 12 Dec 2025 09:40:20 +0000

When life sciences companies talk about digital transformation, they often focus on technology first. But the reality is that the right talent matters just as much as the software. Hiring skilled developers or data scientists is only half the story. If your team doesn't understand the regulatory landscape, compliance protocols, and the high stakes of the industry, even the best technology can slow you down or introduce risk.

A full-stack developer who doesn't know HIPAA or GxP can create bottlenecks instead of accelerating progress. A Salesforce admin unfamiliar with Veeva can introduce errors in workflows that must remain validated. These gaps aren't minor - they can compromise project timelines, audit readiness, and even patient safety.

Generic IT staffing models often fall short because they prioritize technical skills over domain knowledge. Certifications in cloud platforms, programming languages, or AI frameworks are valuable, but they do not prepare candidates for the realities of working in regulated clinical, research, or commercial environments.

At Newpage, we define domain-ready talent as professionals who bring both technical expertise and deep regulatory understanding. Our teams know how to work in validated systems, document code according to FDA standards, and support workflows that comply with 21 CFR Part 11. They understand that every change, every workflow, and every integration must be auditable, secure, and compliant.

Our X-tend model was built specifically to address this challenge. It is an on-demand, pharma-ready staffing framework that extends internal teams with professionals who are compliance-first, platform-certified, and domain-experienced. Talent is evaluated not just on resumes but through scenario-based assessments, GxP training, and real-world experience across multiple systems. Soft skills, communication, and the ability to work in regulated environments are part of the hiring DNA.

The results speak for themselves. Domain-ready talent accelerates project delivery, reduces regulatory risk, and improves audit outcomes. Whether you need developers, QA engineers, or AI specialists, having the right people in the right roles ensures that compliance is built into the workflow, not treated as an afterthought.

Hiring in life sciences isn't about checking boxes for technical skills. It's about ensuring that every professional on your team understands the rules, knows how to work in validated systems, and can contribute safely and efficiently from day one.

In our latest blog, we explore why life sciences companies need domain-ready tech talent, what makes someone truly ready for regulated environments, and how frameworks like X-tend help teams accelerate without compromising compliance.

Read the full article here: https://newpage.io/resources/blogs/why-life-sciences-companies-need-domain-ready-tech-talent-not-just-techies/

Why Pharma Integrations Fail Quietly and What CTOs Need to Watch For

Newpage Solutions — Thu, 04 Dec 2025 17:09:44 +0000

When we work with pharmaceutical and biotech teams, one thing becomes clear very quickly. The biggest challenges are rarely about the individual systems. They are almost always about how those systems connect. Integration is the foundation, yet it is also the area that gets rushed, patched, or treated like a technical side task.

From the outside, integration looks simple. Move data from point A to point B and keep things in sync. But inside a real life sciences ecosystem, nothing stays simple. Workflows evolve, regulations get tighter, APIs change versions, and new systems enter the stack. When this happens, even small cracks in the integration layer start to expose much bigger risks.

We see this often with point to point connections. They begin as quick solutions but turn into sprawling webs that are almost impossible to manage. A small change in Salesforce can trigger updates across multiple downstream systems. Each update needs coordination across teams and vendors, which slows delivery and increases the chances of errors. What started as a shortcut becomes a long term source of complexity.

Another issue we repeatedly encounter is delayed validation thinking. In pharma, integration work touches validated systems. When teams validate too late or skip documentation during early stages, the risk to compliance becomes real. Missing evidence, untracked transformations, or inconsistent logs can create major problems during audits.

There is also the challenge of ad hoc mapping during development sprints. It feels efficient in the moment, especially when teams are trying to meet deadlines. But over time, these shortcuts lead to misaligned data definitions, broken reporting, and silent corruption that no one detects until it becomes a much larger issue.

Even the build versus buy decision creates friction. Teams often prefer to build quick scripts or custom connectors. These look fine at first but rarely scale well. They struggle with error handling, monitoring, and compliance checks. When the business grows or new markets get added, these custom pieces start failing quietly in the background.

At Newpage, we have seen how these patterns impact digital programs. We have also seen how the right integration strategy can completely transform the way clinical, commercial, and safety systems work together. The strongest architectures are always modular, platform agnostic, well governed, and built with compliance in mind from day one. They reduce risk, improve data quality, and support long term digital maturity.

Read the full blog here for a clear breakdown of the most common integration mistakes CTOs face and the steps that prevent them.

How to Know if Your Digital Partner Is Truly Pharma Ready

Newpage Solutions — Thu, 04 Dec 2025 17:09:18 +0000

If you work in life sciences, you already know that digital transformation is not simply about picking the right platform. It is about choosing a partner who understands what it means to build inside a regulated environment. That single choice often determines whether your program moves forward smoothly or turns into a cycle of rework, audit findings, or blocked releases.

What we see far too often is this. A vendor claims to be life sciences ready because they have built a hospital workflow or configured a CRM for a generic healthcare client. Once the project begins, their lack of domain fluency shows up quickly. Basic configurations ignore audit trail requirements. Integrations are built without understanding validation. Teams fail to anticipate quality gate reviews. The result is frustration, delays, and unnecessary risk for the sponsor.

At Newpage, we have worked across pharma, biotech, and MedTech programs, and we have seen the difference a truly pharma ready partner makes. These partners think in terms of traceability, risk, and compliance before they think about features. They understand that a small change in a validated system is not "just a quick update".

They respect how interconnected clinical, commercial, and safety ecosystems are and design systems that protect, not disrupt, regulatory readiness.

One of the clearest signals is how a partner behaves during the earliest conversations. The right partner will ask about quality systems, documentation templates, validation approach, and release controls before proposing any blueprint. They will talk about the impact of an integration on validated states. They will ask how your teams handle deviations, approvals, and sign offs. These are the conversations that show you whether a partner understands the environment they are stepping into.

Another marker is scalability. In pharma, timelines shift quickly due to submissions, inspections, and launch cycles. A partner who cannot scale responsibly, or who cannot onboard teams into validated environments fast enough, becomes a bottleneck rather than an enabler. This is something we have helped clients navigate repeatedly, especially during post acquisition integrations and global rollouts.

Most importantly, pharma ready partners have references that reflect work in regulated environments. Not generic testimonials, but endorsements from QA, regulatory, or safety leaders. If a partner cannot demonstrate success under those conditions, it is a sign to look deeper.

If you are in the process of evaluating vendors, we have broken down the six most reliable signs of a pharma ready digital partner in a detailed guide. It is based on real project experience, real risks, and real lessons from global programs that had no room for error. It will help you recognise the difference between generalist capability and regulated readiness.

Read the full blog here: https://newpage.io/resources/blogs/what-makes-a-digital-partner-pharma-ready/

What Sets Xtend Talent Apart? The 6-Point Vetting Process Explained

Newpage Solutions — Tue, 02 Dec 2025 16:11:20 +0000

Across the life sciences industry, every team is in a race against time. Commercial teams need specialists who can work inside validated systems. Clinical teams need engineers who can document correctly and pass audits without handholding. Data and AI teams need architects who can build responsibly in environments where privacy and traceability matter as much as performance.

Most enterprises know these demands well. What they struggle with is finding people who can operate at this level. Not because there is a shortage of talent, but because there is a shortage of the right kind of talent. Skills alone do not make someone pharma ready. Compliance thinking, documentation discipline, and domain context make the difference between delivery that moves forward and delivery that must be redone.

This gap is the reason X-tend exists at Newpage. When we built this model, the goal was simple. Provide teams who already understand the rules, expectations, and risks that define work in regulated environments. Over time, this became a broader capability. Today, X-tend is not just a staffing model. It is a way of making sure that every resource who joins a project arrives ready to contribute on day one.

One of the things we have seen repeatedly is that traditional hiring funnels simply do not work for pharma and biotech programs. They assess technical skill, but they do not test how someone writes audit-ready documentation, how they think about change control, or how they behave inside a validated pipeline. These gaps only become visible once a project is already in motion. By then, timelines slip, quality issues surface, and compliance teams lose confidence.

Our view is that this risk is avoidable. With the right vetting, training, and onboarding process, teams can integrate new talent without slowing down. That is exactly what we designed X-tend for.
Before someone is deployed, they are tested for domain fluency, documentation capability, communication clarity, and the ability to operate within strict quality systems. They also go through a short but focused onboarding sprint that gives them context for compliance, platform expectations, and client specific workflows. It is a practical way to ensure that talent is not just skilled, but ready.

The result is simple. Teams move faster without cutting corners. Quality improves. Risk decreases. Projects avoid the hidden delays that come from rework, incomplete documentation, or misunderstood requirements.

If you are scaling AI programs, modernising cloud infrastructure, or
expanding commercial platforms, the difference between success and frustration often comes down to the people you place on the work. In life sciences, talent is not interchangeable. It is foundational.

We break down how X-tend works and what makes this model different in our full blog. If you want a deeper look into the six point vetting process and why it matters, you can read the complete piece here:https://newpage.io/resources/blogs/xtend-talent-flexible-it-staffing-for-pharma-and-life-sciences/

Getting FDA-Approved Companies Ready for Digital in 90 Days

Newpage Solutions — Tue, 02 Dec 2025 16:09:46 +0000

Digital transformation is no longer optional in life sciences. Even FDA-approved companies that have passed audits and met compliance standards often find themselves struggling with outdated systems, disconnected data, and manual workflows. Compliance alone doesn't make you digitally ready. To compete and innovate, you need platforms that are integrated, scalable, and built to accelerate operations without compromising regulations.

At Newpage, we've designed a 90-day plan specifically for FDA-regulated companies to move from assessment to implementation quickly, safely, and at scale. The goal isn't just to check boxes - it's to create systems that actually work together, support your teams, and prepare your company for the next wave of digital innovation.

It starts with understanding where you are today. A full digital readiness assessment evaluates your IT landscape, integration maturity, and compliance posture across systems like Salesforce, Veeva, and ERP platforms. With a clear baseline and heatmaps of opportunity, stakeholders can align on priorities and start planning with measurable outcomes in mind.

Next comes mapping your roadmap and picking the right platforms. Hybrid or cloud-first architectures, integration tools, and low-code/no-code frameworks are considered alongside KPIs for success, including audit traceability, cycle times, and user adoption. Using practical templates and fit-gap analyses, companies can build realistic, compliant plans that connect business goals with technical realities.

The 90-day sprint continues with pilot implementations, validation blueprints, and integration. By choosing high-impact use cases and using agile frameworks, teams can test workflows, automate processes, and validate everything from user requirements to operational protocols. Prebuilt accelerators help link CRM, PV, and R&D functions while maintaining encryption, audit trails, and secure access controls.

Finally, the plan culminates in training, compliance handover, and go-live. By the end of the 12 weeks, teams are empowered, systems are integrated, and digital processes are not only compliant but ready to scale. Real-world results speak for themselves. Companies have seen faster patient onboarding, smoother audits, and fully connected Salesforce and clinical trial systems in record time.

FDA approval isn't the finish line. Without digital readiness, compliance can slow you down instead of speeding innovation. The Newpage 90-day model combines the discipline of life sciences with the speed of startups to deliver systems that are compliant, connected, and built for the future.

In our latest blog, we show how FDA-regulated companies can move from manual and disconnected processes to fully integrated digital systems in just 90 days. We cover the stages, frameworks, and outcomes that make transformation fast, safe, and measurable.

Read the full blog here:https://newpage.io/resources/blogs/how-fda-approved-companies-can-become-digitally-ready-in-90-days/

How GenAI Is Transforming Medical Information in Pharma

Newpage Solutions — Tue, 02 Dec 2025 16:08:17 +0000

Medical Information (Med-Info) teams are the first point of contact for healthcare professionals seeking answers about drug safety, dosing, or trial details. But with growing drug portfolios and rising enquiry volumes, traditional manual triage methods are struggling. Sorting through thousands of questions by hand not only slows down response times but also increases stress for teams and risks compliance gaps.

That's where AI can make a real difference. At Newpage, we've seen how GenAI can be embedded into Med-Info workflows to deliver speed, accuracy, and compliance at scale. It's not about replacing humans - it's about amplifying their impact.

The key is to start with the right design and governance. For one global pharmaceutical company, Newpage helped set up a GenAI triage engine integrated with their Salesforce Service Cloud. This system could categorize enquiries, flag safety or off-label issues, and route questions to the right team automatically. Human reviewers stayed in the loop, which not only built trust but also provided feedback to continually improve the AI's performance.

Results speak for themselves. The company reduced response times by 65%, cut down manual workload, and created a workflow that was fully auditable and compliant. Reviewers could focus on high-value content while the AI handled repetitive triage. Even better, the company was able to expand the system to multiple languages and continuously validate it to meet global regulatory standards.

The success of this approach highlights some key lessons for pharma leaders exploring AI in Med-Info: start with human-in-the-loop models, invest in prompt engineering for accuracy, account for multilingual workflows, and embed continuous validation. When done right, AI moves Med-Info from a reactive support function to a predictive, data-driven capability.

This use case shows that speed and scale do not have to come at the cost of compliance. With the right partner, governance, and strategy, AI can help pharma teams work smarter, not harder, and maintain the trust that is critical in healthcare.

Read the full blog here: https://newpage.io/resources/blogs/case-study-using-ai-to-triage-medical-information-requests/

How to Build Responsible AI for Life Sciences

Newpage Solutions — Tue, 02 Dec 2025 16:04:35 +0000

AI has enormous potential in life sciences. From speeding up drug discovery to improving patient care, the opportunities are real. But in an industry where human health and regulatory compliance are on the line, the stakes are high. A poorly designed AI system can do more harm than good, creating compliance risks, misleading results, or even patient safety issues.

At Newpage, we've seen how pharma and biotech teams can move beyond the hype and make AI work in real-world, regulated environments. The key isn't just technical capability; it's responsibility by design. AI systems must be transparent, auditable, and aligned with human oversight at every stage.

Before deploying AI, pharma leaders need to understand several critical factors. Start with the use case and the potential impact. Know who the AI affects, what the worst-case scenario could be, and how humans need to be involved. Explainable models, audit-ready workflows, and robust bias testing are essential for building trust with medical teams and regulators.

Governance is another pillar. Setting up cross-functional councils with compliance, data science, legal, and medical representation ensures that AI systems are reviewed for ethical, clinical, and regulatory concerns. Transparent data practices and ongoing monitoring for model drift keep AI systems reliable over time.

Equally important is preparing your teams. AI isn't just for engineers. Medical affairs, safety, and regulatory teams need to understand what AI can and cannot do, how to validate outputs, and when to escalate concerns. Human-in-the-loop processes ensure that decisions affecting patients are always supervised.

When done right, AI in life sciences doesn't just accelerate workflows. It builds trust, strengthens compliance, and gives teams the confidence to act on insights quickly. The most successful projects aren't the flashy demos - they're the quietly reliable systems that earn the confidence of clinicians, regulators, and patients alike.

In our latest blog, we break down the ten essential steps for building AI in life sciences that is responsible, auditable, and compliant. We look at what it takes to move from experimentation to operational use without compromising ethics or safety.

Read the full article here:https://newpage.io/resources/blogs/how-to-build-responsible-ai-for-life-sciences/

Talent as a Growth Lever: Scaling Life-Sciences Engineering in Weeks, Not Months

Newpage Solutions — Tue, 02 Dec 2025 15:45:59 +0000

In life sciences, speed and flexibility can be the difference between meeting a critical Phase II trial deadline and falling behind. But building a capable engineering team in a highly regulated environment is rarely fast. Biotech companies often face a dual challenge: finding engineers who understand modern software development and who also know the rules that govern healthcare and patient data.

A US-based biotech recently faced this exact dilemma. Their scientific teams were top-notch, but the digital engineering setup wasn’t ready for the next stage of their data-driven therapeutic program. Waiting for traditional hiring cycles — often 8 to 12 weeks — wasn’t an option. They needed engineers who could immediately work on cloud-native architectures, microservices, DevOps pipelines, and compliance-heavy workflows.

This is where Newpage’s X-Tend Talent Services made the difference. Within three weeks, a full engineering unit was mobilised, embedded, and contributing value. The approach wasn’t just about speed; it was about matching domain-ready talent with precise business outcomes.

Key steps included:

Curated, domain-aware talent — Engineers with experience in regulated digital health environments, fluent in agile methods and modern stacks, were selected to ensure minimal ramp-up time.
Rapid onboarding framework — Instead of standard onboarding, the team completed orientation and domain immersion within one week, and design kick-offs by week three.
Embedded collaboration — The engineers worked within the client’s existing squads, adopting the same Jira boards, sprint cadence, and review processes.
Compliance baked in — Every engineer understood data privacy, audit trails, and security baselines, reducing downstream remediation risks.

The results were tangible. By week three, the client was reviewing design artefacts and MVP backlog items. By week six, the patient-support platform backend was live in a staging environment, and early user testing had begun. Time-to-team was cut by 60 percent, the platform release accelerated, and regulatory risk was kept under control. Internal leadership could focus on architecture and strategy rather than onboarding and first-level hiring.

For CTOs and tech leaders in life sciences, there are a few key takeaways: define engineering outcomes first, partner with talent providers who understand the domain, embed teams early into existing agile processes, and plan for flexibility to scale up or down without friction.

Talent is more than a resource — it is a growth lever. When life sciences companies combine domain knowledge with engineering excellence, they don’t just hire faster; they build faster, safer, and smarter.

In our latest blog, we walk through how a US biotech used X-Tend Talent Services to scale an engineering team in just three weeks, deliver critical modules, and accelerate its digital ecosystem. We explore the challenges, deployment strategy, and the measurable business impact.

Read the full article here: https://newpage.io/resources/blogs/talent-as-a-growth-lever-how-xtend-helped-a-us-biotech-scale-engineering-in-3-weeks/

What CIOs Need to Know Before Buying AI in Healthcare

Newpage Solutions — Mon, 24 Nov 2025 16:19:41 +0000

AI in healthcare is having a moment, but not for the reasons most people think. The industry has moved past the excitement of flashy demos. CIOs and CDS teams have seen enough pilots that never scaled to last a lifetime. What matters now is technology that works in the real world, safely, and at scale.

That distinction is critical. Life sciences is highly regulated and deeply process driven. Any system that touches patient data, medical content, or regulatory workflows has to operate within those constraints. Compliance, safety, and reliability are not optional features — they are foundations.

The conversation is no longer about what AI can do. It is about what it can do responsibly, repeatably, and in alignment with regulations. At Newpage, we see too many AI programs evaluated purely on features, speed, or hype. The reality is that readiness matters more: clean data, trained teams, aligned workflows, and clear governance make the difference between a tool that falters and one that transforms operations.

Responsible use also requires asking the right questions: How does the system explain its decisions? How is bias mitigated? How is regulatory drift tracked and controlled? In healthcare, these are not abstract considerations — they determine whether an AI project succeeds or fails under real-world conditions.

The best AI programs in life sciences are those where leaders invest early in readiness. Once processes, data, and human oversight are in place, AI stops being experimental and becomes operational. It accelerates delivery, reduces errors, and strengthens decision-making — all without compromising compliance.

In our latest blog, we break down the eight critical considerations CIOs should have before buying AI for healthcare. We look at readiness, compliance, risk, and how to move from pilots to scalable platforms while maintaining accountability.

Read the full article here: What CIOs Need to Know Before Buying AI in Healthcare

The Med Info Bottleneck Is Real. Here Is How AI Can Actually Fix It!

Newpage Solutions — Mon, 24 Nov 2025 14:38:11 +0000

Anyone who has worked in pharmaceutical Med Info knows the pressure. Teams are buried under daily HCP queries, safety related questions, and urgent requests that demand accurate, consistent, and fully compliant responses. What many people outside the function do not realize is that Med Info is often one of the most manually overloaded parts of the medical ecosystem.

At Newpage, we work closely with Med Info, Medical Affairs, PV, and commercial teams, and the pattern is always the same. Workloads rise faster than headcount, triage delays slow down response times, and even the most experienced specialists end up spending hours on tasks that should have been automated years ago.

This is exactly why Salesforce AgentHub is getting so much attention in life sciences. Not because it replaces medical expertise, but because it supports it in a structured, compliant, and traceable way.

What stands out to us at Newpage is not the AI part itself, but how AgentHub fits inside the existing Salesforce ecosystem. Med Info teams already live in platforms like Service Cloud, Health Cloud, and Experience Cloud. The real value is when automation operates inside those established systems, not around them.

When we evaluate Med Info maturity for clients, the first question we ask is not about AI. It is about content structure, approval paths, pharmacovigilance routing, and validation readiness. Without these fundamentals, automation cannot scale safely. AgentHub works best when the foundation is strong, and that is where most transformation efforts need direction. For life sciences teams working in regulated environments, a structured readiness plan becomes essential. You can explore a detailed 90-day roadmap here.

Another thing that often gets overlooked is the compliance angle. In pharma, every system needs to be explainable, traceable, and easy to audit. AgentHub’s biggest advantage is that it works inside Salesforce, which means audit trails, access controls, and event logs are already part of the process. For Med Info leaders who struggle with consistency and documentation, this becomes a real game changer.

If there is one message we always give our clients at Newpage, it is this: automation is not about speed alone. It is about reducing risk, strengthening scientific accuracy, and freeing skilled reviewers to focus on what truly requires expertise. AI is the assistive layer, not the replacement.

Read the full article here: Automating Med Info with Salesforce Agenthub

How to select a Salesforce Partner for your Lifescience Organisation

Newpage Solutions — Mon, 24 Nov 2025 14:35:51 +0000

If you work in life sciences, you already know this truth. Every technology decision has regulatory weight. Every workflow connects to compliance. Every piece of data has the potential to affect patient safety.

So when teams think about choosing a Salesforce implementation partner, it is surprising how often the conversation gets reduced to rates, resumes, and certifications. In a regulated world, the partner you select is not just a vendor. They influence your audit readiness, your data hygiene, and the overall maturity of your digital operations.

At Newpage, we meet life sciences leaders who have inherited broken CRM implementations, missing validation documents, poor adoption, or data models that make AI impossible. None of this happens because the technology was wrong. Most of the time, it is because the partner did not understand the domain.

The disconnect usually begins early. A partner might be strong in Salesforce but completely new to pharmacovigilance workflows. Or they might understand HCP engagement but overlook the role of data lineage. Or they position UAT as the place where all regulatory questions will be solved. In life sciences, these gaps become expensive, and sometimes, irreversible.

What teams really need is a partner who treats compliance and domain context as the foundation, not a phase. Someone who understands how medical affairs functions differ from commercial field teams, how safety cases move across systems, how validations should be documented, how integrations are audited, and how UX directly affects data quality.

These are not platform skills. These are life sciences skills.

And that is the real message behind our new blog at Newpage. It serves as a practical guide for CIOs, CRM owners, and delivery leads who are navigating this decision. The blog breaks down the hidden factors that often get ignored, the questions teams should be asking during vendor selection, and the signals that indicate whether a partner truly understands the regulatory and operational realities of life sciences.

If your organization is preparing for a CRM transformation, scaling medical operations, or planning for AI-driven workflows, this guide will help you make a more informed choice. Because the right partner will accelerate value, reduce risk, and create systems that stand up to audits. The wrong one will leave you with technical debt, frustrated teams, and a future that becomes harder to scale.

Your CRM will become a living system. It will influence compliance, customer intelligence, and how your teams collaborate. Make the selection with the seriousness it deserves.

Read the full blog here: How to Select a Salesforce Partner for Your Pharma Organisation